As an expert in reliability data engineering and analytics, this role leads the design, governance, and evolution of enterprise data capabilities that support PG&E’s reliability and resilience strategy. Based in Oakland with a hybrid work model, you will build scalable data solutions that integrate multi-source datasets for performance assessment, risk modeling, and long-term grid planning.
Role Overview
You will serve as a recognized industry authority in reliability data engineering and analytics, setting technical direction for how reliability data and data pipelines are developed, integrated, and managed. The position emphasizes data integrity, auditability, and readiness for operational, regulatory, and strategic use across the organization.
The work includes defining a technical vision and establishing industry-leading practices for reliability data systems, ensuring rigorous standards for data transformation, metadata management, and data lineage. You will also act as an advisor to senior leadership on data strategy, data risk, and reliability performance insights.
Responsibilities
- Form and lead teams focused on complex, data and analytics-centric problems with broad impact requiring in-depth analysis and judgment.
- Contribute to solving uniquely complex data and analytics-centric issues with significant organizational impact.
- Provide thought leadership on infrastructure that enables big data access and analysis with verified data quality and appropriately captured, cataloged metadata.
- Partner with business and other departments to develop requirements and translate them into complex cross-functional systems.
- Assist other programmers/analysts with unusual or complex problems spanning multiple functional and technology areas.
- Coordinate with other departments on cross-team work needs and requirements.
- Drive departmental standards, norms, and new goals or objectives.
- Communicate recommendations both orally and in writing.
- Mentor and guide less experienced colleagues.
Required Qualifications
- BA/BS in Computer Science, Management Information Systems, related field of study, or equivalent experience.
- Ten years of experience with multiple data engineering and ETL ecosystems, including Palantir Foundry, Spark, Informatica, SAP BODS, and OBIEE.
- Proven track record implementing data warehouses and data lakes within the previous five years.
- Experience leading development teams.
- Three years of experience in machine learning algorithm deployment and machine learning operations.
- Master’s degree in Computer Science, Management Information Systems, or related field, or equivalent experience.
Technologies and Tools
- Palantir Foundry, Spark, Informatica, SAP BODS, OBIEE
- Unit testing, CI/CD, source control
- Data warehouses, data lakes
- Machine learning algorithm deployment, machine learning operations
- Big data, data transformation
- Metadata management, data lineage
- Business intelligence and data access tool
Department Context
This role sits within the System Performance, Reliability and Resiliency Strategy team in the Electric Transmission and Distribution Engineering organization. The Reliability Data team is responsible for developing and curating reliability data and data pipelines to meet auditable standards.
Work Model and Location
- Hybrid work model requiring in-office attendance at least two or three days per week.
- Additional remote days may be available based on business needs.
- Headquarters is located in the Oakland General Office.
Compensation and Benefits
- Salary range: USD 155,000 - 265,000 per year
- Bay Area minimum: $155,000
- Bay Area mid-point: $210,000
- Bay Area maximum: $265,000
Benefits include discretionary incentive compensation programs.
Knowledge, Skills, Abilities, and Competencies
- Business intelligence and data access tool expertise.
- Knowledge of software engineering principles such as unit testing, CI/CD, and source control.
