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# Head of Data & BI Platform Engineering

- **Company:** Irca. Pfizer
- **Location:** San Diego, CA, United States
- **Experience:** Expert
- **Salary:** $274,000.0
- **Contract:** Permanent contract
- **Skills:** Training Data, Query Performance, Artificial Intelligence, Data Analysis, Systems Engineering, Audit Trail, Microsoft Azure, Cloud Computing, Information Systems, Computer Networks, Databases, Data Centers, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Warehousing, Digital Assets, Graph Database, Design of User Interfaces, Human-Computer Interaction, Identity and Access Management, Systems Analysis, Machine Learning, Metadata, Meta-Data Management, Metadata Repositories, Neo4j, Platform as a Service (PAAS), Performance Tuning, Reliability Engineering, Power BI, Tableau (Software), Privacy Controls, Computer Network Operations, Cloud Platform System, Feature Engineering, Informatica Powercenter, System Availability, Snowflake, Data Lakes, Semi-structured Data, Core Data, Information Technology, Data Lineage, Star Schema, Data Management, Data Lakehouse, Spotfire, Azure Synapse Analytics, Multiplatform, Looker Analytics, Data Pipelines, GXP, TIBCO (Software), Mulesoft, Alteryx, Amazon Redshift, Databricks
- **Published:** July 31, 2026
- **Apply:** https://www.careerbuilder.com/job-details/head-of-data-bi-platform-engineering-la-jolla-ca--387c5dcf-9db9-4387-8b3d-8a15a19b71a3

## About the Role

* Master's degree in Computer Science, Information Systems, Engineering, or a related discipline. Significant relevant experience with a Bachelor's degree may be considered in lieu of a Master's degree.
 * 15+ years (or 13+ with a Master's degree) 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 GxP 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 LookML, AtScale) 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 FinOps practices for cloud data platform cost governance.
 * Experience with modern data stack architectures including data mesh, data lakehouse, and medallion architecture patterns., Access Control, Analysis Skills, Artificial Intelligence (AI), Auditing, Best Practices, Biology, Budgeting, Business Intelligence, Cloud Computing, Coaching, Communication Skills, Computer Networks, Computer Science, Computer Systems, Contract Management, Cross-Functional, Customer Acquisition, Data Analysis, Data Lake, Data Management, Data Modeling, Data Quality, Data Warehousing, Database Extract Transform and Load (ETL), Enterprise Architecture, Enterprise Protection, FDA (Food and Drug Administration), Federal Laws and Regulations, Government, GxP, HIPAA (Health Insurance Portability and Accountability Act), Healthcare, Healthcare Providers, Incentive Programs, Incident Response, Informatica, Leadership, Licensing, Looker, Machine Learning, Machine Tool, Matrix Management, Metadata, Metrics, Microsoft Windows Azure, Multiplatform/Cross-Platform, Neo4j, Network Operations Center, On Call, Ontology, Performance Metrics, Performance Tuning/Optimization, Platform as a Service (PaaS),
Policy Implementation, Power BI, Privacy Controls, Privacy Regulations, Quality Management, Quality Monitoring, Regulations, Regulatory Compliance, Regulatory Requirements, Reliability Engineering, Service Level Agreement (SLA), Snowflake Schema, Stardog, State Laws and Regulations, Structured Data, Systems Administration/Management, Systems Analysis, Systems Engineering, Tableau, Team Lead/Manager, Technical Strategy, Technology Analysis, Tibco Spotfire, Transformation Tools, User Interface/Experience (UI/UX), Vendor/Supplier Licensing, Vendor/Supplier Relations

## Description

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 (CoE) 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.

ROLE SUMMARY

This role has direct ownership accountability for the following 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, FiveTran, 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, SciBite, 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., 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 CoE Platform Reliability / SRE function.
 * Drive platform cost transparency and FinOps 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 CoE 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.


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