Lead Engineer Data & AI Governance

Phillips 66 & YOU - Together we can fuel the future   Phillips 66 is seeking a Lead Data & AI Governance Engineer to lead the development of governance policies, standards, control frameworks, and operating models required to enable reliable AI-driven access to data within our Enterprise Data Platform. This role is responsible for establishing enterprise governance frameworks, defining accountability structures, and driving strategic alignment across business, IT, Enterprise Architecture, SAP, ETRM, Enterprise MDM, Information Security, and platform engineering teams. The successful candidate will help translate governance objectives into practical enterprise standards, controls, roadmaps, and operating processes that ensure Enterprise Data Platform assets are discoverable, understandable, trustworthy, and fit for AI-driven use.   What You’ll Do   Governance Strategy & Operating Model

Lead development of governance policies, standards, frameworks, and operating models supporting Enterprise Data Platform Governance. Establish governance metrics, certification criteria, accountability models, and compliance monitoring processes. Define governance requirements for metadata, data quality, stewardship, data modeling, and AI readiness. Drive governance adoption through stakeholder engagement, training, communications, and change management.

Data Reliability Governance

Establish enterprise frameworks for Data Quality, Data Stewardship, Data Certification, Data Lineage, Data Observability, Compliance Monitoring Define enterprise baseline data quality requirements and control standards. Establish stewardship responsibilities, escalation paths, and issue-resolution processes.

Data Modeling & Metadata Governance

Define Enterprise Data Platform standards for Data Modeling, Naming Conventions, Common Identifiers, Units of Measure, Dataset Linking, Semantic Modeling, Metadata Management Define governance requirements for Business Context Metadata, Data Discovery Metadata, and Data Model Metadata.

Enterprise Data Foundation Strategy

Partner with SAP, ETRM, Enterprise MDM, Enterprise Architecture, and platform engineering teams to assess opportunities for reusable enterprise data foundations. Define long-term strategies for shared datasets, reference data, master data, standardized hierarchies, and cross-domain interoperability. Develop roadmap recommendations that improve data reuse, integration, analytics, and AI-driven access across the Enterprise Data Platform.

Security, Risk & Compliance

Partner with Information Security and appropriate enterprise stakeholders to define governance requirements for Data Classification, Access Control, Retention & Archival, Regulatory Compliance Ensure governance controls align with enterprise policies and compliance requirements.

What You’ll Bring – Required

Legally authorized to work in the job posting country. Bachelor’s degree in Computer Science, Information Systems or a related field. 6+ years of experience in data governance, data management, data architecture, data engineering, or related disciplines. 3+ years’ experience implementing governance capabilities within enterprise data platforms. 3+ years of hands-on experience with Databricks, Unity Catalog, Genie, Python, and SQL.

What Makes You Stand Out – Preferred

Experience leading enterprise data governance programs within large or regulated organizations. Experience implementing Data Quality and Stewardship frameworks Experience with Enterprise MDM, Master Data, or Reference Data initiatives Experience working with SAP and ETRM platforms Experience with Databricks Unity Catalog, Genie, Metric Views, and Semantic Modeling Experience supporting AI-enabled analytics and enterprise data consumption Background in energy, manufacturing, logistics, or other asset-intensive industries

Compensation Range  This position has a base salary range of $ 160,200 – $195,800.