Principal, Data Engineer - Reliability Data

PG&E is hiring a Principal, Data Engineer focused on reliability data engineering and analytics in Oakland, CA (hybrid).

Responsibilities

• Form and lead teams tackling complex data and analytics-centric challenges with broad, significant impact
• Resolve uniquely complex data and analytics problems requiring in-depth analysis and judgment
• Provide thought leadership on infrastructure to enable big data access and analysis with verified data quality and properly captured, cataloged metadata
• Partner with the business and other departments to translate requirements into complex cross-functional systems
• Support programmers/analysts on unusual or complex problems spanning multiple functional and technology areas
• Coordinate with other departments to meet cross-team work needs and requirements
• Drive departmental standards, norms, and new goals/objectives
• Communicate recommendations through oral and written channels
• Mentor and guide less experienced colleagues

Requirements

• BA/BS in Computer Science, Management Information Systems, related field of study, or equivalent experience
• Minimum 10 years of experience with multiple data engineering/ETL ecosystems, including:
  • Palantir Foundry
  • Spark
  • Informatica
  • SAP BODS
  • OBIEE
• Proven track record of successfully implementing data warehouses/data lakes over the previous five years
• Experience leading development teams
• 3 years of experience in machine learning algorithm deployment and machine learning operations
• Master’s degree in Computer Science, Management Information Systems, related field, or equivalent experience

Key Technologies

• Palantir Foundry, Spark, Informatica, SAP BODS, OBIEE
• Unit testing, CI/CD, source control
• Data warehouses, data lakes, big data, data transformation
• Metadata management, data lineage
• Business intelligence and data access tool
• Machine learning algorithm deployment, machine learning operations

About the Team

• The System Performance, Reliability and Resiliency Strategy team is part of PG&E’s Electric Transmission and Distribution Engineering organization
• Team mission includes planning, organizing, and managing resources to execute PG&E’s Electric Reliability Strategy and initiatives
• The Reliability Data team curates reliability data and data pipelines to meet auditable standards

Position Summary

• Recognized industry expert in reliability data engineering and analytics
• Leads design, governance, and advancement of enterprise data capabilities supporting PG&E’s reliability and resilience strategy
• Defines technical vision and establishes practices for integration and management of reliability data and data pipelines
• Ensures data integrity, auditability, and readiness for operational, regulatory, and strategic use
• Architects and delivers scalable data solutions integrating multi-source datasets for reliability performance assessment, risk modeling, and long-term grid planning
• Establishes standards for data transformation, metadata management, and data lineage aligned to enterprise data governance frameworks and regulatory requirements
• Improves transparency, traceability, and decision-quality through innovation in data engineering approaches
• Advises senior leadership on data strategy, data risk, and reliability performance insights
• Represents PG&E in technical forums and standards bodies to advance best practices in reliability data management and analytics

Work Model

• Hybrid role based in Oakland, CA (Oakland General Office)
• In-office requirement: at least 2 to 3 days per week
• Remaining days may be worked remotely depending on business needs

Department & Job Details

• Job Category: Information Technology
• Job Level: Manager/Principal
• Business Unit: Strategy & Growth
• Work Type: Hybrid
• Job Location: Oakland

Salary & Incentives

• Salary range (Bay Area): $155,000 to $265,000 per year
• Mid-point: $210,000 per year
• Discretionary incentive compensation programs

Education & Additional Competencies

• Business Intelligence and data access tool expertise
• Knowledge of software engineering principles including unit testing, CI/CD, and source control