Expert, Data Engineer - Reliability Data
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. Serves as a recognized subject matter expert in the design, development, and governance of reliability data and data pipelines supporting enterprise reliability and resilience strategy. Leads the architecture and delivery of scalable data solutions that extract, transform, and integrate complex data from diverse sources into high-quality, auditable datasets. Ensures data is accurate, consistent, and structured to support critical analysis, regulatory requirements, and strategic decision-making. Establishes and enforces standards for data engineering, transformation logic, and metadata management, including comprehensive data lineage and audit documentation. Drives continuous improvement in data quality, pipeline performance, and governance practices to meet evolving regulatory and business needs. Provides technical leadership across the data lifecycle, guiding teams in the implementation of best practices and resolving complex data challenges. Partners closely with cross-functional teams, data owners, and senior leadership to ensure reliability data solutions align with enterprise objectives and PG&E’s Electric Reliability Strategy. Delivers expert-level insight into data integrity, risk, and compliance, enabling trusted, transparent decision-making. Represents the organization in internal and external forums, contributing to industry best practices in reliability data management and analytics. This position follows a hybrid work model, requiring employees to report to their assigned office location at least two or three days per week. The remaining days may be worked remotely, depending on business needs. The headquarters is located in the Oakland General Office.
Requirements
- BA/BS in Computer Science, Management Information Systems, related field of study, or equivalent experience.
- 7 years of experience with data engineering/ETL ecosystem, such as Palantir Foundry, Spark, Informatica, SAP BODS, OBIEE.
- Experience with multiple data engineering/ETL ecosystems.
- Experience with machine learning algorithm deployment.
Nice To Haves
- Master’s degree in Computer Science, Management Information Systems, or related field, or equivalent experience.
- Experience leading development teams.
Responsibilities
- Leads a team on moderately complex to complex data and analytics-centric problems having a broad impact that require in-depth analysis and judgment to obtain results or solutions.
- May contribute to the resolution of uniquely complex data and analytics-centric problems having a significant impact
- Identifies, designs, and implements internal process improvements, including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes.
- Resolves application programming analysis problems of broad scope within procedural guidelines.
- Assists other programmers/analysts on unusual or especially complex problems that cross multiple functional/technology areas.
- Conceptualizes and generates infrastructure that allows big data to be accessed and analyzed with verified data quality, and metadata is appropriately captured and cataloged.
- Collaborates with peers to develop departmental standards, norms, and new goals/objectives.
- Plans work to meet assigned general objectives; reviews progress regularly, and solutions may provide an opportunity for creative/non-standard approaches.
- Assesses data pipeline performance and suggests/implements changes as required.
- Communicates (oral and written) recommendations.
- Mentors/guides less experienced colleagues.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Associate degree
