Head of Data & BI Platform Engineering in Tadworth

Role Summary

The Head of Data & BI Platform Engineering owns Pfizer's enterprise data and business intelligence platform layer.

This encompasses the platforms on which Pfizer's structured and semi-structured data is stored, processed, transformed, and visualized, including the organization's core data warehousing and lake platforms (such as Snowflake and Databricks), data integration and transformation tools (such as Alteryx and Mulesoft), and enterprise BI and visualization platforms (such as Tableau, Power BI, and Spotfire).

Pfizer's AI & Data Center of Excellence (Co E) exists to accelerate the Enterprise AI Strategy, enabling every function, every builder, and every decision‑maker to work faster and with greater precision.

At the foundation of that strategy is data: well‑structured, governed, and readily accessible data that AI systems, analytics teams, and business leaders can depend on.

The data platforms this leader manages are a critical upstream dependency for the majority of AI workloads across Pfizer, making the reliability, performance, and governance of these platforms a direct enabler of the organization's AI ambitions.

In this role, you will lead a team of engineers and platform specialists across and will be accountable for delivering these platforms as enterprise services with published SLAs, governed access, and measurable value to the federated AI and analytics teams that depend on them.

• Platform Categories
• Data Warehousing and Lakehouse Platforms
• Enterprise data warehouse and lakehouse platforms (e. g., Snowflake, Databricks, Amazon Redshift) including infrastructure, administration, performance tuning, cost governance, and access management.
• Unified storage and compute environments for structured, semi‑structured, and large‑scale analytical data workloads across all divisions.
• Data Integration and Transformation
• Data pipeline and integration tooling (e. g., Alteryx, dbt, Five Tran, Databricks, or equivalent) including pipeline development standards, orchestration, and operational monitoring.
• ETL/ELT framework governance, enabling self‑service data preparation for analysts while maintaining data quality and lineage standards.
• Knowledge graph, ontology, and semantic model tooling (e. g., Neo4J, Sci Bite, Stardog, Neptune, etc.).
• Business Intelligence and Visualization Platforms
• Enterprise BI and visualization platforms (e. g., Tableau, Power BI, Spotfire) including platform administration, licensing governance, performance, and user access.
• Semantic layer and report governance standards, in partnership with the AI Ready Data team, to ensure consistent and trusted metric definitions across the enterprise.
• Data Catalog and Observability
• Data catalog tooling and metadata management, enabling data discoverability and lineage tracking across the platform estate.
• Platform observability and data reliability engineering including SLA monitoring, data quality alerting, and incident response.

Key Responsibilities

• Platform Leadership and Strategy
• Define and own the Data & BI platform strategy and multi‑year roadmap, ensuring platform investments are aligned to the needs of federated AI and analytics teams across Pfizer.
• Lead, develop, and grow a team of engineers and platform specialists across Platform Operations, Platform Development, and Data Reliability pods.
• Establish and maintain product‑minded ownership of the platform portfolio with roadmap priorities driven by user needs, validated through regular engagement with platform consumers.
• Own the vendor relationships and licensing strategy for the data and BI platform portfolio, including contract management, performance governance, and technology evaluation.
• Partner with the Head of AI Ready Data to ensure platform infrastructure and data governance standards are tightly integrated, the platform must serve AI‑ready data, not just available data.
• Platform Engineering and Operations
• Oversee the design, build, and operation of enterprise data pipelines, warehouse/lakehouse environments, and BI infrastructure at scale.
• Define and publish platform SLAs covering availability, data freshness, query performance, and pipeline reliability and hold the team accountable to them.
• Establish data reliability engineering practices including error budgets, on‑call processes, incident response, and blameless post‑mortems, in coordination with the Co E Platform Reliability / SRE function.
• Drive platform cost transparency and Fin Ops practices ensuring compute and storage costs are visible, attributed, and continuously optimized.
• Ensure all platforms meet Pfizer's enterprise security, privacy, and regulatory compliance requirements, in partnership with the CISO organization and Trusted AI team.
• Stakeholder Engagement and Adoption
• Serve as the primary platform interface for federated AI and analytics teams across Pfizer, proactively embedding platform support and enabling self‑service access.
• Partner with Enterprise Architecture and existing Pfizer Digital & Technology data teams to ensure the Co E platform extends and modernizes existing data infrastructure investments rather than duplicating them.
• Contribute to the AI & Data Guild network, enabling cross‑functional awareness of platform capabilities, best practices, and available data assets.
• Report regularly to the Chief AI and Data Officer on platform health, SLA performance, adoption metrics, and investment priorities.
• Basic Qualifications
• Master’s degree in Computer Science, Information Systems, Engineering, or a related discipline; or equivalent years of experience.
• 15+ years of progressive experience in data engineering, data platform architecture, or enterprise analytics infrastructure, with a minimum of 5 years in a senior engineering leadership role.
• Demonstrated hands‑on experience administering and scaling enterprise data warehousing or lakehouse platforms at scale, including at least one of the following: Snowflake, Databricks, Amazon Redshift, or Azure Synapse.
• Proven experience managing enterprise BI and visualization platforms (e. g., Tableau, Power BI, or Spotfire), including governance, performance, and adoption programs.
• Experience with data integration and pipeline tooling (e. g., Alteryx, dbt, Informatica, Fivetran, or equivalent) in a large enterprise context.
• Proven track record of leading platform teams with an SLA‑driven, product‑minded operating model with documented outcomes in platform reliability, cost efficiency, and user adoption.
• Strong command of data catalog, metadata management, data lineage, and data quality frameworks in enterprise environments.
• Experience establishing platform governance in regulated industries, including data privacy controls, access management, and audit trail requirements.
• Demonstrated ability to lead through influence in a federated organizational model — driving adoption through value delivery and user experience, not mandate.
• Exceptional communication skills, with the ability to translate platform strategy and technical trade‑offs for both technical teams and executive stakeholders.
• Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.
• Preferred Qualifications
• Experience in the biopharmaceutical, life sciences, or healthcare sector, with familiarity with Gx P data requirements, HIPAA, and FDA data integrity expectations.
• Experience supporting AI and machine learning workflows as a data platform consumer understanding of feature engineering pipelines, training data requirements, and model data dependencies.
• Familiarity with semantic layer tools (e. g., dbt metrics layer, Looker Look ML, At Scale) and governed metric management.
• Experience operating within or alongside a Center of Excellence or shared services model in a large, matrixed organization.
• Working knowledge of Fin Ops practices for cloud data platform cost governance.
• Experience with modern data stack architectures including data mesh, data lakehouse, and medallion architecture patterns.
• Other Job Details
• Last Day to Apply: 7/28/2026
• Work Location Assignment: Hybrid

The annual base salary for this position ranges from $274,000.00 to $456,600.00.* In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 30.0% of the base salary and eligibility to participate in our share based long term incentive program.

We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments.

Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage.

Learn more at Pfizer Candidate Site – U.

Benefits | (uscandidates. mypfizerbenefits. com).

Pfizer compensation structures and benefit packages are aligned based on the location of hire.

The United States salary range provided does not apply to Tampa, FL or any location outside of the United States. * The annual base salary for this position in Tampa, FL ranges from $246,600.00 to $411,000.00.

This role is posted in multiple locations.

If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U. S. by any employer.

U. S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations.

These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure.

Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act.

Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government.

If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status.

Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA.

Pfizer is an E-Verify employer.

This position requires permanent work authorization in the United States.

Pfizer endeavors to make www. pfizer. com/careers accessible to all users.

If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer. com.

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Requests for any other reason will not be returned.

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.

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