Principal, Data Engineer - Reliability Data

PG&E•Oakland, CA

9h•Hybrid

About The Position

The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E’s Electric Reliability Strategy and initiatives. Within this department the Reliability Data team is on point for a key role is developing and curating all reliability data and data pipelines so that they meet auditable standards. This position serves as a recognized industry expert in reliability data engineering and analytics, leading the design, governance, and advancement of enterprise data capabilities that underpin PG&E’s reliability and resilience strategy. It defines the technical vision and establishes industry-leading practices for the development, integration, and management of reliability data and data pipelines, ensuring data integrity, auditability, and readiness for critical operational, regulatory, and strategic use. The role leads the architecture and delivery of advanced, scalable data solutions that integrate complex, multi-source datasets to support reliability performance assessment, risk modeling, and long-term grid planning. It establishes and enforces rigorous standards for data transformation, metadata management, and data lineage, ensuring compliance with regulatory requirements and alignment with enterprise data governance frameworks. The role drives innovation in data engineering approaches to enhance transparency, traceability, and decision-quality across the organization. It acts as a trusted advisor to senior leadership, providing expert guidance on data strategy, data risk, and reliability performance insights. It influences enterprise decision-making by ensuring data solutions effectively support PG&E’s Electric Reliability Strategy and investment priorities. The role builds and maintains strong relationships with internal stakeholders, external partners, and industry organizations, and represents PG&E in technical forums and standards bodies, contributing to the advancement of best practices in reliability data management and analytics.

Requirements

BA/BS in Computer Science, Management Information Systems, related field of study, or equivalent experience.
Ten years of experience with multiple data engineering/ETL ecosystems such as Palantir Foundry, Spark, Informatica, SAP BODS, and OBIEE.
Experience with multiple data engineering/ETL ecosystems.
Proven track record of successfully implementing data warehouses/data lakes over the previous five years.
Experience leading development teams.
Three years of experience in machine learning algorithm deployment and machine learning operations.

Nice To Haves

Master’s degree in Computer Science, Management Information Systems, or related field, or equivalent experience.
Business Intelligence and data access tool expertise.
Knowledge of software engineering principles such as unit testing, CI/CD, and source control.

Responsibilities

Forms and leads teams to focus on complex data and analytics-centric problems with broad and significant impacts requiring in-depth analysis and judgment to obtain results or solutions.
Contributes to resolving uniquely complex data and analytics-centric problems that have a significant impact.
Provides thought leadership on infrastructure that allows big data to be accessed and analyzed with verified data quality and metadata appropriately captured and cataloged.
Partners with the business and other departments to develop requirements and apply them to create complex cross-functional systems.
Assists other programmers/analysts on unusual or complex problems that cross multiple functional/technology areas.
Works closely with other departments on cross-team work needs/requirements.
Drives the development of departmental standards, norms, and new goals/objectives.
Communicates (oral and written) recommendations.
Mentors/guides less experienced colleagues.