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Vice President, Build — Data, Engineering & AI跳至主要内容#Vice President, Build — Data, Engineering & AI page is loaded## Vice President, Build — Data, Engineering & AI申请locations: United Kingdom - Walton Oaks: Europe - Any Pfizer Sitetime type: 全职posted on: 今天发布job requisition id: 4960896Role purposeThe VP, Build — Data, Engineering & AI is the owner of the International Commercial build engine, accountable for turning prioritized demand into trusted, reusable and production-grade data, AI agents, solutions and technical services. The role owns the International commercial data foundation, engineering pool, solution architecture, AI evaluation, AgentOps, production run, technical standards, vendor/Systems Integrator delivery model and CIO-platform integration. Its mandate is to deliver speed without fragmentation, reuse without bureaucracy, and innovation with evidence, reliability, compliance and cost discipline.Enterprise scope and impactThis is a Vice President-level enterprise build role spanning the full path from data foundation to production AI. The role operates with senior stakeholders across International Commercial, CIO, CMO, Legal/Compliance, Finance, markets, strategic vendors and SI partners, with accountability for technical strategy, delivery capacity, production quality, run economics and integration with Pfizer’s enterprise platform standards.Operating-design safeguardsData Architect operates horizontally across the four Build sub-pillars to protect semantic standards, AI-ready criteria and data quality.Solution Architect operates horizontally to ensure solutions compose the data foundation, AICL and enterprise platform spine consistently.AI Evaluation & Assurance remains independent of builders and owns the evidence pack for ship/no-ship decisions.Product & Delivery leadership manages roadmap translation, scrum/programme delivery and capacity transparency across pods.Key responsibilities & accountabilitiesThe data foundationBuild the trusted commercial data foundation: L1–L4 squads working to one standard (the four data layers, raw to ready-to-use), including reporting & BI and the knowledge & unstructured squad that underpins retrieval quality for the AI Capability Library (AICL).Own semantic standards, inheritance rules and AI-ready criteria through the Data Architect; run the Collibra dictionary, master & reference data operations and the governance council.Own data quality and observability: shift-left checks, lineage and monitoring built in, not bolted on.Run data BAU — incidents, refreshes and access — baselined before any cost reduction is taken.Own data products and their owners (global and above-market, including the Customer / CRM and CFC (Customer Facing Colleagues) reporting products), with business data stewards dotted in from markets and functions.Manage the data-supply vendor relationships (IQVIA, Komodo, Optum, Veeva, etc..): data and delivery contracts, one door to Procurement.Engineering & AIOwn solution architecture: how solutions compose the data, the AICL and the platform, including model-tier selection — mirroring the Data Architect on the data side.Run one shared, deployable engineering pool crewed into pods; Systems Integration partners and contractors crew in — never as standing outside teams. Engineering talent is never fragmented, and capacity decisions are transparent against the agreed portfolio priority queue.Own product and delivery management: roadmap and translation on the way in; scrum and programme delivery on the way through.Build the agent library and standards; deliver the reusable data agents of the AICL and their agent-facing data contracts.Run AI evaluation and assurance independently of the builders: evals, red teaming, model-tier proof and the clearance evidence pack.Own AgentOps and technical run: agents and classic ML in production, AI cost operations, and solution run & support.The CIO seamOwn platform integration and the model gateway — routing each task to the right model, including small language models (SLMs) where quality holds.Be the one voice to the CIO on the platform spine; land the commercial data foundation as a certified source on Loom, including the Collibra-to-Loom reconciliation.Run & BAUKeep what is live running well: program support, maintenance, upgrades and data quality across the estate.Keep AI running costs visible and managed, feeding the cost signal back to Strategy, Value & Innovation.Key relationships & interfacesInternalHead of Business Transformation & Technology — International Commercial Division (direct line); peer for Strategy, Value & Innovation and Adoption & Scale.The CIO organisation — the platform spine and its milestone plan.Pillar 1 — one priority queue in, engineering capacity out; pods owned by Pillar 1 product owners and crewed from this pillar.Pillar 3 — hand-offs into adoption, localisation and the in-market network for everything shipped.Global Commercial Analytics — data scientists, engineers and project managers crewing into pods via the operating agreement.Legal & Compliance — privacy engineering dotted in for consent, PII and lawful basis.ExternalData-supply vendors (IQVIA, Komodo, Optum, Veeva) and SI partners (e.g. Accenture, Deloitte) crewing into the pool.Model and platform vendors through the CIO's model-access framework.Success measuresPrioritized use cases delivered to production with named owner, evidence pack, run model and sunset criteria.Data quality, lineage and observability coverage across priority data products.Time from funded demand to production.Production reliability, incident rate and support performance.AI evaluation coverage, red-team completion and model-tier proof before ship.Cost-to-serve, model-routing savings and reuse of AICL / agent patterns across markets.Leadership behaviours (Pfizer values)Courage — holds one priority queue against pressure from every direction and protects data from losing attention to the agent flagship.Excellence — one standard across the four layers; evaluation independent of the builders; production quality as a habit.Equity — one deployable pool serving all markets and functions, not the best-connected ones.Joy — engineers doing their best work in small, empowered pods, with agents drafting first-pass code and people reviewing, hardening and owning.Scope & decision rightsDecides technical architecture and standards from raw data to running agent, within the CIO platform guardrails.Owns delivery capacity allocation and crewing recommendations against the agreed portfolio priority queue, with escalation where demand exceeds capacity or technical risk changes sequencing.Owns the ship/no-ship evidence pack through independent evaluation; Legal & Compliance clears on that evidence.Owns data-supply and Systems Integrator vendor selection and contracts, with Procurement.Escalates to the Head of Business Transformation & Technology — International Commercial Division where priority conflicts exceed the plan of record.Experience & qualifications15+ years across data engineering and AI/ML or software delivery, with senior leadership of both data and engineering organisations — the rare end-to-end profile this role deliberately demands.A track record of building governed data platforms at enterprise scale (semantic layers, data products, quality and observability) and of shipping AI or agentic solutions into production.Experience running large engineering organisations (~50–100 including partners) as a flexible pool — pods, squads, deployable capacity — rather than fixed project teams.Vendor and SI management at scale, including data and delivery contracts.Prior senior leadership (Senior Director / VP level) in biopharma or another regulated data environment strongly preferred; degree in a technical discipline required, advanced degree preferred.Proven ability to operate as a senior enterprise leader in a complex global matrix, influencing senior business, technology, legal/compliance, medical, finance, PX and market stakeholders without relying solely on direct authority.Technical skills & knowledgeModern data architecture: layered data platforms (raw to ready-to-use), governed semantics, data contracts, catalogues (e.g. Collibra), lineage and observability.Agentic AI: agent platforms and registries, model gateways and model-tier selection including SLMs, evaluation and red-teaming practice, AgentOps and production ML.Cloud data and analytics stacks (e.g. Snowflake) and integration with enterprise data fabrics.AI cost operations: metering, routing and cost-per-outcome management.Engineering leadership: agile delivery at scale, platform engineering, DevOps and run practices.Purpose Breakthroughs that change patients' lives... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives. Digital Transformation StrategyOne bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.Flexibility We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation! Equal Employment Opportunity We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms – allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.DisAbility ConfidentWe are proud to be a Disability Confident Employer and we encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments necessary to support your application and future career. Our mission is unleashing the power of our people, especially those with unique superpowers. Your journey with Pfizer starts here!To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. #J-18808-Ljbffr

\n Vice President, Build — Data, Engineering & AI\n We’re in relentless pursuit of breakthroughs that change patients’ lives. We innovate every day to make the world a healthier place. \n To fully realize Pfizer’s purpose – Breakthroughs that change patients’ lives – we have established a clear set of expectations regarding “what” we need to achieve for patients and “how” we will go about achieving those goals. \n Pfizer offers competitive compensation and benefits programs designed to meet the diverse needs of our colleagues. \n The VP, Build — Data, Engineering & AI is the owner of the International Commercial build engine, accountable for turning prioritized demand into trusted, reusable and production-grade data, AI agents, solutions and technical services. The role owns the International commercial data foundation, engineering pool, solution architecture, AI evaluation, AgentOps, production run, technical standards, vendor/Systems Integrator delivery model and CIO-platform integration. Its mandate is to deliver speed without fragmentation, reuse without bureaucracy, and innovation with evidence, reliability, compliance and cost discipline. Enterprise scope and impact\n This is a Vice President-level enterprise build role spanning the full path from data foundation to production AI. The role operates with senior stakeholders across International Commercial, CIO, CMO, Legal/Compliance, Finance, markets, strategic vendors and SI partners, with accountability for technical strategy, delivery capacity, production quality, run economics and integration with Pfizer’s enterprise platform standards. Operating‑design safeguards\n Data Architect operates horizontally across the four Build sub-pillars to protect semantic standards, AI‑ready criteria and data quality. \n Solution Architect operates horizontally to ensure solutions compose the data foundation, AICL and enterprise platform spine consistently. \n AI Evaluation & Assurance remains independent of builders and owns the evidence pack for ship/no-ship decisions. \n Product & Delivery leadership manages roadmap translation, scrum/programme delivery and capacity transparency across pods. Key responsibilities & accountabilities The data foundation\n Build the trusted commercial data foundation: L1–L4 squads working to one standard (the four data layers, raw to ready‑to‑use), including reporting & BI and the knowledge & unstructured squad that underpins retrieval quality for the AI Capability Library (AICL). \n Own semantic standards, inheritance rules and AI-ready criteria through the Data Architect; run the Collibra dictionary, master & reference data operations and the governance council. \n Own data quality and observability: shift‑left checks, lineage and monitoring built in, not bolted on. \n Run data BAU — incidents, refreshes and access — baselined before any cost reduction is taken. \n Own data products and their owners (global and above‑market, including the Customer / CRM and CFC (Customer Facing Colleagues) reporting products), with business data stewards dotted in from markets and functions. \n Manage the data‑supply vendor relationships (IQVIA, Komodo, Optum, Veeva, etc): data and delivery contracts, one door to Procurement. \n Own solution architecture: how solutions compose the data, the AICL and the platform, including model‑tier selection — mirroring the Data Architect on the data side. \n Run one shared, deployable engineering pool crewed into pods; Systems Integration partners and contractors crew in—never as standing outside teams. Engineering talent is never fragmented, and capacity decisions are transparent against the agreed portfolio priority queue. \n Own product and delivery management: roadmap and translation on the way in; scrum and programme delivery on the way through. \n Build the agent library and standards; deliver the reusable data agents of the AICL and their agent‑facing data contracts. \n Run AI evaluation and assurance independently of the builders: evals, red‑team, model‑tier proof and the clearance evidence pack. \n Own AgentOps and technical run: agents and classic ML in production, AI cost operations, and solution run & support. The CIO seam\n Own platform integration and the model gateway — routing each task to the right model, including small language models (SLMs) where quality holds. \n Be the one voice to the CIO on the platform spine; land the commercial data foundation as a certified source on Loom, including the Collibra‑to‑Loom reconciliation. \n Keep what is live running well: program support, maintenance, upgrades and data quality across the estate. \n Keep AI running costs visible and managed, feeding the cost signal back to Strategy, Value & Innovation. Key relationships & interfaces Internal\n Head of Business Transformation & Technology — International Commercial Division (direct line); peer for Strategy, Value & Innovation and Adoption & Scale. \n The CIO organisation — the platform spine and its milestone plan. \n Pillar 1 — one priority queue in, engineering capacity out; pods owned by Pillar 1 product owners and crewed from this pillar. \n Pillar 3 — hand‑offs into adoption, localisation and the in‑market network for everything shipped. \n Global Commercial Analytics — data scientists, engineers and project managers crewing into pods via the operating agreement. \n Legal & Compliance — privacy engineering dotted in for consent, PII and lawful basis. External\n Data‑supply vendors (IQVIA, Komodo, Optum, Veeva) and SI partners (e.g. Accenture, Deloitte) crewing into the pool. \n Model and platform vendors through the CIO's model‑access framework. Success measures\n Prioritized use cases delivered to production with named owner, evidence pack, run model and sunset criteria. \n Data quality, lineage and observability coverage across priority data products. \n Time from funded demand to production. \n Production reliability, incident rate and support performance. \n AI evaluation coverage, red‑team completion and model-tier proof before ship. \n Cost-to-serve, model-routing savings and reuse of AICL / agent patterns across markets. \n Courage — holds one priority queue against pressure from every direction and protects data from losing attention to the agent flagship. \n Excellence — one standard across the four layers; evaluation independent of the builders; production quality as a habit. \n Equity — one deployable pool serving all markets and functions, not the best‑connected ones. \n Joy — engineers doing their best work in small, empowered pods, with agents drafting first‑pass code and people reviewing, hardening and owning. \n Decides technical architecture and standards from raw data to running agent, within the CIO platform guardrails. \n Owns delivery capacity allocation and crewing recommendations against the agreed portfolio priority queue, with escalation where demand exceeds capacity or technical risk changes sequencing. \n Owns the ship/no‑ship evidence pack through independent evaluation; Legal & Compliance clears on that evidence. \n Owns data‑supply and Systems Integrator vendor selection and contracts, with Procurement. \n Escalates to the Head of Business Transformation & Technology — International Commercial Division where priority conflicts exceed the plan of record. Qualifications\n 15+ years across data engineering and AI/ML or software delivery, with senior leadership of both data and engineering organisations — the rare end‑to‑end profile this role deliberately demands. \n A track record of building governed data platforms at enterprise scale (semantic layers, data products, quality and observability) and of shipping AI or agentic solutions into production. \n Experience running large engineering organisations (~50–100 including partners) as a flexible pool — pods, squads, deployable capacity — rather than fixed project teams. \n Vendor and SI management at scale, including data and delivery contracts. \n Prior senior leadership (Senior Director/VP level) in biopharma or another regulated data environment strongly preferred; degree in a technical discipline required, advanced degree preferred. \n Proven ability to operate as a senior enterprise leader in a complex global matrix, influencing senior business, technology, legal/compliance, medical, finance, PX and market stakeholders without relying solely on direct authority. Technical skills & knowledge\n Modern data architecture: layered data platforms (raw to ready‑to‑use), governed semantics, data contracts, catalogues (e.g. Collibra), lineage and observability. \n Agentic AI: agent platforms and registries, model gateways and model-tier selection including SLMs, evaluation and red‑teaming practice, AgentOps and production ML. \n Cloud data and analytics stacks (e.g. Snowflake) and integration with enterprise data fabrics. \n AI cost operations: metering, routing and cost-per-outcome management. \n Engineering leadership: agile delivery at scale, platform engineering, DevOps and run practices. Disability Confident\n We are proud to be a Disability Confident Employer and we encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments necessary to support your application and future career. \n Our mission is unleashing the power of our people, especially those with unique superpowers. Your journey with Pfizer starts here! \n We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this in all its forms – allowing us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees. \n #J-18808-Ljbffr

We’re in relentless pursuit of breakthroughs that change patients’ lives. We innovate every day to make the world a healthier place. To fully realize Pfizer’s purpose – Breakthroughs that change patients’ lives – we have established a clear set of expectations regarding “what” we need to achieve for patients and “how” we will go about achieving those goals. Pfizer offers competitive compensation and benefits programs designed to meet the diverse needs of our colleagues. The VP, Build — Data, Engineering & AI is the owner of the International Commercial build engine, accountable for turning prioritized demand into trusted, reusable and production-grade data, AI agents, solutions and technical services. The role owns the International commercial data foundation, engineering pool, solution architecture, AI evaluation, AgentOps, production run, technical standards, vendor/Systems Integrator delivery model and CIO-platform integration. Its mandate is to deliver speed without fragmentation, reuse without bureaucracy, and innovation with evidence, reliability, compliance and cost discipline. This is a Vice President-level enterprise build role spanning the full path from data foundation to production AI. The role operates with senior stakeholders across International Commercial, CIO, CMO, Legal/Compliance, Finance, markets, strategic vendors and SI partners, with accountability for technical strategy, delivery capacity, production quality, run economics and integration with Pfizer’s enterprise platform standards. Data Architect operates horizontally across the four Build sub-pillars to protect semantic standards, AI‑ready criteria and data quality. Solution Architect operates horizontally to ensure solutions compose the data foundation, AICL and enterprise platform spine consistently. AI Evaluation & Assurance remains independent of builders and owns the evidence pack for ship/no-ship decisions. Product & Delivery leadership manages roadmap translation, scrum/programme delivery and capacity transparency across pods. Build the trusted commercial data foundation: L1–L4 squads working to one standard (the four data layers, raw to ready‑to‑use), including reporting & BI and the knowledge & unstructured squad that underpins retrieval quality for the AI Capability Library (AICL). Own semantic standards, inheritance rules and AI-ready criteria through the Data Architect; run the Collibra dictionary, master & reference data operations and the governance council. Own data quality and observability: shift‑left checks, lineage and monitoring built in, not bolted on. Run data BAU — incidents, refreshes and access — baselined before any cost reduction is taken. Own data products and their owners (global and above‑market, including the Customer / CRM and CFC (Customer Facing Colleagues) reporting products), with business data stewards dotted in from markets and functions. Manage the data‑supply vendor relationships (IQVIA, Komodo, Optum, Veeva, etc): data and delivery contracts, one door to Procurement. Own solution architecture: how solutions compose the data, the AICL and the platform, including model‑tier selection — mirroring the Data Architect on the data side. Run one shared, deployable engineering pool crewed into pods; Systems Integration partners and contractors crew in—never as standing outside teams. Engineering talent is never fragmented, and capacity decisions are transparent against the agreed portfolio priority queue. Own product and delivery management: roadmap and translation on the way in; scrum and programme delivery on the way through. Build the agent library and standards; deliver the reusable data agents of the AICL and their agent‑facing data contracts. Run AI evaluation and assurance independently of the builders: evals, red‑team, model‑tier proof and the clearance evidence pack. Own AgentOps and technical run: agents and classic ML in production, AI cost operations, and solution run & support. Own platform integration and the model gateway — routing each task to the right model, including small language models (SLMs) where quality holds. Be the one voice to the CIO on the platform spine; land the commercial data foundation as a certified source on Loom, including the Collibra‑to‑Loom reconciliation. Keep what is live running well: program support, maintenance, upgrades and data quality across the estate. Keep AI running costs visible and managed, feeding the cost signal back to Strategy, Value & Innovation. Head of Business Transformation & Technology — International Commercial Division (direct line); peer for Strategy, Value & Innovation and Adoption & Scale. The CIO organisation — the platform spine and its milestone plan. Pillar 1 — one priority queue in, engineering capacity out; pods owned by Pillar 1 product owners and crewed from this pillar. Pillar 3 — hand‑offs into adoption, localisation and the in‑market network for everything shipped. Global Commercial Analytics — data scientists, engineers and project managers crewing into pods via the operating agreement. Legal & Compliance — privacy engineering dotted in for consent, PII and lawful basis. Data‑supply vendors (IQVIA, Komodo, Optum, Veeva) and SI partners (e.g. Accenture, Deloitte) crewing into the pool. Model and platform vendors through the CIO's model‑access framework. Prioritized use cases delivered to production with named owner, evidence pack, run model and sunset criteria. Data quality, lineage and observability coverage across priority data products. Time from funded demand to production. Production reliability, incident rate and support performance. AI evaluation coverage, red‑team completion and model-tier proof before ship. Cost-to-serve, model-routing savings and reuse of AICL / agent patterns across markets. Courage — holds one priority queue against pressure from every direction and protects data from losing attention to the agent flagship. Excellence — one standard across the four layers; evaluation independent of the builders; production quality as a habit. Equity — one deployable pool serving all markets and functions, not the best‑connected ones. Joy — engineers doing their best work in small, empowered pods, with agents drafting first‑pass code and people reviewing, hardening and owning. Decides technical architecture and standards from raw data to running agent, within the CIO platform guardrails. Owns delivery capacity allocation and crewing recommendations against the agreed portfolio priority queue, with escalation where demand exceeds capacity or technical risk changes sequencing. Owns the ship/no‑ship evidence pack through independent evaluation; Legal & Compliance clears on that evidence. Owns data‑supply and Systems Integrator vendor selection and contracts, with Procurement. Escalates to the Head of Business Transformation & Technology — International Commercial Division where priority conflicts exceed the plan of record. 15+ years across data engineering and AI/ML or software delivery, with senior leadership of both data and engineering organisations — the rare end‑to‑end profile this role deliberately demands. A track record of building governed data platforms at enterprise scale (semantic layers, data products, quality and observability) and of shipping AI or agentic solutions into production. Experience running large engineering organisations (~50–100 including partners) as a flexible pool — pods, squads, deployable capacity — rather than fixed project teams. Vendor and SI management at scale, including data and delivery contracts. Prior senior leadership (Senior Director/VP level) in biopharma or another regulated data environment strongly preferred; degree in a technical discipline required, advanced degree preferred. Proven ability to operate as a senior enterprise leader in a complex global matrix, influencing senior business, technology, legal/compliance, medical, finance, PX and market stakeholders without relying solely on direct authority. Modern data architecture: layered data platforms (raw to ready‑to‑use), governed semantics, data contracts, catalogues (e.g. Collibra), lineage and observability. Agentic AI: agent platforms and registries, model gateways and model-tier selection including SLMs, evaluation and red‑teaming practice, AgentOps and production ML. Cloud data and analytics stacks (e.g. Snowflake) and integration with enterprise data fabrics. AI cost operations: metering, routing and cost-per-outcome management. Engineering leadership: agile delivery at scale, platform engineering, DevOps and run practices. We are proud to be a Disability Confident Employer and we encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments necessary to support your application and future career. Our mission is unleashing the power of our people, especially those with unique superpowers. Your journey with Pfizer starts here! We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this in all its forms – allowing us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees. #J-18808-Ljbffr

Vice President, Build — Data, Engineering & AI跳至主要内容#Vice President, Build — Data, Engineering & AI page is loaded## Vice President, Build — Data, Engineering & AI申请locations: United Kingdom - Walton Oaks: Europe - Any Pfizer Sitetime type: 全职posted on: 今天发布job requisition id: 4960896Role purposeThe VP, Build — Data, Engineering & AI is the owner of the International Commercial build engine, accountable for turning prioritized demand into trusted, reusable and production-grade data, AI agents, solutions and technical services. The role owns the International commercial data foundation, engineering pool, solution architecture, AI evaluation, AgentOps, production run, technical standards, vendor/Systems Integrator delivery model and CIO-platform integration. Its mandate is to deliver speed without fragmentation, reuse without bureaucracy, and innovation with evidence, reliability, compliance and cost discipline.Enterprise scope and impactThis is a Vice President-level enterprise build role spanning the full path from data foundation to production AI. The role operates with senior stakeholders across International Commercial, CIO, CMO, Legal/Compliance, Finance, markets, strategic vendors and SI partners, with accountability for technical strategy, delivery capacity, production quality, run economics and integration with Pfizer’s enterprise platform standards.Operating-design safeguardsData Architect operates horizontally across the four Build sub-pillars to protect semantic standards, AI-ready criteria and data quality.Solution Architect operates horizontally to ensure solutions compose the data foundation, AICL and enterprise platform spine consistently.AI Evaluation & Assurance remains independent of builders and owns the evidence pack for ship/no-ship decisions.Product & Delivery leadership manages roadmap translation, scrum/programme delivery and capacity transparency across pods.Key responsibilities & accountabilitiesThe data foundationBuild the trusted commercial data foundation: L1–L4 squads working to one standard (the four data layers, raw to ready-to-use), including reporting & BI and the knowledge & unstructured squad that underpins retrieval quality for the AI Capability Library (AICL).Own semantic standards, inheritance rules and AI-ready criteria through the Data Architect; run the Collibra dictionary, master & reference data operations and the governance council.Own data quality and observability: shift-left checks, lineage and monitoring built in, not bolted on.Run data BAU — incidents, refreshes and access — baselined before any cost reduction is taken.Own data products and their owners (global and above-market, including the Customer / CRM and CFC (Customer Facing Colleagues) reporting products), with business data stewards dotted in from markets and functions.Manage the data-supply vendor relationships (IQVIA, Komodo, Optum, Veeva, etc..): data and delivery contracts, one door to Procurement.Engineering & AIOwn solution architecture: how solutions compose the data, the AICL and the platform, including model-tier selection — mirroring the Data Architect on the data side.Run one shared, deployable engineering pool crewed into pods; Systems Integration partners and contractors crew in — never as standing outside teams. Engineering talent is never fragmented, and capacity decisions are transparent against the agreed portfolio priority queue.Own product and delivery management: roadmap and translation on the way in; scrum and programme delivery on the way through.Build the agent library and standards; deliver the reusable data agents of the AICL and their agent-facing data contracts.Run AI evaluation and assurance independently of the builders: evals, red teaming, model-tier proof and the clearance evidence pack.Own AgentOps and technical run: agents and classic ML in production, AI cost operations, and solution run & support.The CIO seamOwn platform integration and the model gateway — routing each task to the right model, including small language models (SLMs) where quality holds.Be the one voice to the CIO on the platform spine; land the commercial data foundation as a certified source on Loom, including the Collibra-to-Loom reconciliation.Run & BAUKeep what is live running well: program support, maintenance, upgrades and data quality across the estate.Keep AI running costs visible and managed, feeding the cost signal back to Strategy, Value & Innovation.Key relationships & interfacesInternalHead of Business Transformation & Technology — International Commercial Division (direct line); peer for Strategy, Value & Innovation and Adoption & Scale.The CIO organisation — the platform spine and its milestone plan.Pillar 1 — one priority queue in, engineering capacity out; pods owned by Pillar 1 product owners and crewed from this pillar.Pillar 3 — hand-offs into adoption, localisation and the in-market network for everything shipped.Global Commercial Analytics — data scientists, engineers and project managers crewing into pods via the operating agreement.Legal & Compliance — privacy engineering dotted in for consent, PII and lawful basis.ExternalData-supply vendors (IQVIA, Komodo, Optum, Veeva) and SI partners (e.g. Accenture, Deloitte) crewing into the pool.Model and platform vendors through the CIO's model-access framework.Success measuresPrioritized use cases delivered to production with named owner, evidence pack, run model and sunset criteria.Data quality, lineage and observability coverage across priority data products.Time from funded demand to production.Production reliability, incident rate and support performance.AI evaluation coverage, red-team completion and model-tier proof before ship.Cost-to-serve, model-routing savings and reuse of AICL / agent patterns across markets.Leadership behaviours (Pfizer values)Courage — holds one priority queue against pressure from every direction and protects data from losing attention to the agent flagship.Excellence — one standard across the four layers; evaluation independent of the builders; production quality as a habit.Equity — one deployable pool serving all markets and functions, not the best-connected ones.Joy — engineers doing their best work in small, empowered pods, with agents drafting first-pass code and people reviewing, hardening and owning.Scope & decision rightsDecides technical architecture and standards from raw data to running agent, within the CIO platform guardrails.Owns delivery capacity allocation and crewing recommendations against the agreed portfolio priority queue, with escalation where demand exceeds capacity or technical risk changes sequencing.Owns the ship/no-ship evidence pack through independent evaluation; Legal & Compliance clears on that evidence.Owns data-supply and Systems Integrator vendor selection and contracts, with Procurement.Escalates to the Head of Business Transformation & Technology — International Commercial Division where priority conflicts exceed the plan of record.Experience & qualifications15+ years across data engineering and AI/ML or software delivery, with senior leadership of both data and engineering organisations — the rare end-to-end profile this role deliberately demands.A track record of building governed data platforms at enterprise scale (semantic layers, data products, quality and observability) and of shipping AI or agentic solutions into production.Experience running large engineering organisations (~50–100 including partners) as a flexible pool — pods, squads, deployable capacity — rather than fixed project teams.Vendor and SI management at scale, including data and delivery contracts.Prior senior leadership (Senior Director / VP level) in biopharma or another regulated data environment strongly preferred; degree in a technical discipline required, advanced degree preferred.Proven ability to operate as a senior enterprise leader in a complex global matrix, influencing senior business, technology, legal/compliance, medical, finance, PX and market stakeholders without relying solely on direct authority.Technical skills & knowledgeModern data architecture: layered data platforms (raw to ready-to-use), governed semantics, data contracts, catalogues (e.g. Collibra), lineage and observability.Agentic AI: agent platforms and registries, model gateways and model-tier selection including SLMs, evaluation and red-teaming practice, AgentOps and production ML.Cloud data and analytics stacks (e.g. Snowflake) and integration with enterprise data fabrics.AI cost operations: metering, routing and cost-per-outcome management.Engineering leadership: agile delivery at scale, platform engineering, DevOps and run practices.Purpose Breakthroughs that change patients' lives... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives. Digital Transformation StrategyOne bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.Flexibility We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation! Equal Employment Opportunity We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms – allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.DisAbility ConfidentWe are proud to be a Disability Confident Employer and we encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments necessary to support your application and future career. Our mission is unleashing the power of our people, especially those with unique superpowers. Your journey with Pfizer starts here!To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers. #J-18808-Ljbffr

Role: Popeyes Team Leader Location: Stowmarket, IP14 5XF Hours: Part-Time Hours Available / Permanent Salary: £13.Bonus Scheme: Bonus Incentive! Company: EG On The Move About the role: As a Popeyes Team Leader, youll be at the forefront of delivering exceptional service and ensuring smooth, efficie

Location: Perth, Scotland Salary: £45,000 - £50,000 plus benefits Summary: Working with a well established manufacturing business, part of a global Group, you will be responsible for managing Customer Services and worldwide Export.Liaising with customers, government border agencies and internal st

Are you a passionate and caring individual looking for a rewarding career with excellent training and opportunities for development? Join Care UK, a multi award winning care provider as a Care Team Leader.The Role Leading and supervising your shift Case managing residents and liaising with families,

JDR Recruitment are recruiting for Cleaning Supervisors for a large distribution centre based in Worcester, WR4.Key Responsibilities Team Leadership Supervise, motivate, and support a team of 5 cleaning operatives.Allocate daily tasks and monitor completion against agreed standards.Conduct team brie

Are you looking for an exciting Room Leader role in a unique Early Years environment based in Surrey? We are looking for an experienced and passionate Room Leader to join the team in Leatherhead, Surrey.This is an exciting opportunity to be part of a high-quality early years provider, offering a nur

The English, Maths and ESOL Team has been established at Carshalton College to bring all ESOL, GCSE and Functional Skills provision together within a single department.Were now seeking a Team Leader - English to join the School Management Team.In this role, youll work closely with the Head of School

We're currently recruiting a dedicated Retail Supervisor to help ensure the smooth running of the operations in CH&CO on a part time basis, contracted to 30 hours per week.As a Retail Supervisor, you will use your skills to maintain a high standard of quality work.In return, you will have the chance

Team Leader nights - Full Time ( 33h or 44h per week) Mill View Care Home - East Grindstead, RH19 4QW Day Shifts - 8:00am to 8:15pm Pay -.Please note this role is not available for sponsorship and we cant offer less than 22 hours a week*.Are you a passionate and caring individual looking for a rewar

We are currently recruiting for a knowledgeable and experienced Electrical Panel Assembly Team Leader to supervise the assembly team responsible for manufacturing and testing power distribution boards (PDBs) installed in UK NHS and private ambulance fleets.This role combines hands-on technical exper

Team Leader/Tractor DriverPosted 22nd July 2026REFERENCE32062_1784709297### Share this job### Relevant JobsFacilities Management including CleaningCustodianLocationIpswich, SuffolkJob TypePermanentAre you passionate about cleanliness, teamwork, and delivering exceptional service? Vertas is looking

Howard Lock Consulting Ltd in London is seeking a Head of Private Banking / Team Leader to drive performance within a leading financial institution.You will lead a high-calibre team of Private Bankers, oversee a growing HNW/UHNW client portfolio, and deliver tailored wealth management solutions.Flue

Senior C# Developer / Team Leader – 450-500 per day.Contract Senior C# Developer – Lead Developer – 80/20 split, ASP.Net, MVC, C#, WEB API, SQL Server, UI, JavaScript, jQuery, Angular JS, Cloud, Azure, Mobile – 450-500 a day (outside IR35) – East Midlands.Global Engineering firm is looking

Team Leader/Tractor DriverPosted 22nd July 2026REFERENCE32062_1784709297### Share this job### Relevant JobsFacilities Management including CleaningCustodianLocationIpswich, SuffolkJob TypePermanentAre you passionate about cleanliness, teamwork, and delivering exceptional service? Vertas is looking

Head of Private Banking / Team Leader.Head of Private Banking / Team Leader.This is an excellent opportunity for a commercially driven private banking professional to lead a high-performing team while managing and growing a portfolio of high-net-worth (HNW) and ultra-high-net-worth (UHNW) clients.Th

TalentPool partners with a globally recognised consumer brand to appoint a Head of IT to lead the UK IT function, managing a team of IT professionals while acting as the key technology partner to the UK leadership team.This role combines IT operations, service delivery, business partnering, and proj

A leading financial services company in Greater London is seeking a Website Lead.This role demands extensive knowledge of Wordpress and excellent communication skills.You will take ownership of the company website, improve performance, and ensure effective information sharing.The position requires a

Greets visitors, manages calls, arranges meetings, handles mail and supports office administration.

Greets visitors, handles inquiries, manages records, and assists with office duties.Requires excellent communication and organizational skills.

Greets visitors, answers queries, manages reception area, and assists with office duties.

This role combines front-of-house customer service with facilities support, managing enquiries, and ensuring a welcoming campus environment.

Seeking a Receptionist/Healthcare Assistant for Optical Express in Dartford, UK.Responsibilities include patient testing, discharging, laser technician duties, and general reception tasks.This is a full-time, permanent role with a salary of £25,400.

The RoleExpress new ideas, take initiative and save lives.Others talk about being brave, at IC24, we’re made that way.From providing high quality integrated urgent care for over six million people, to thinking of innovative solutions for our patients –every role at IC24 is made to be brave.As th

Seeking a friendly and organised Receptionist & Administrative Assistant for a busy school front office.Responsibilities include managing reception, supporting daily tasks, and assisting with school communications and events.

Seeking a Receptionist with Team Assistant duties for a financial services firm in Mayfair, offering training and career growth.

Welcoming guests, handling calls, managing mail and meeting rooms, supporting office events.

Corporate receptionist needed for a global law firm in London, providing 5-star customer service, managing meeting reservations, and supporting administrative tasks.

Seeking an outgoing and proactive Front of House/Facilities Administrator for a part-time role in London.Responsibilities include welcoming visitors, maintaining office organization, and providing administrative support.

Do you embody friendliness, approachability, courtesy, and helpfulness, coupled with exceptional communication skills?.We are looking for a Receptionist that thrives on taking initiative, possesses a flexible work approach, excels at multitasking, and adeptly prioritises tasks.If this sounds like yo

Start Delivering with Uber Eats.Delivering with Uber Eats offers a flexible way of making money.It is a great alternative to traditional part-time delivery jobs or other part-time gigs, temp jobs or seasonal work.See how delivering with the Uber app can help you make money flexibly.You decide how mu

Start Delivering with Uber Eats.Delivering with Uber Eats offers a flexible way of making money.It is a great alternative to traditional part-time delivery jobs or other part-time gigs, temp jobs or seasonal work.See how delivering with the Uber app can help you make money flexibly.You decide how mu

Start Delivering with Uber Eats.Delivering with Uber Eats offers a flexible way of making money.It is a great alternative to traditional part-time delivery jobs or other part-time gigs, temp jobs or seasonal work.See how delivering with the Uber app can help you make money flexibly.You decide how mu

Start Delivering with Uber Eats.Delivering with Uber Eats offers a flexible way of making money.It is a great alternative to traditional part-time delivery jobs or other part-time gigs, temp jobs or seasonal work.See how delivering with the Uber app can help you make money flexibly.You decide how mu

Start Delivering with Uber Eats.Delivering with Uber Eats offers a flexible way of making money.It is a great alternative to traditional part-time delivery jobs or other part-time gigs, temp jobs or seasonal work.See how delivering with the Uber app can help you make money flexibly.You decide how mu