Associate, Data Engineer - Reliability Data

Requisition ID # 172360 

Job Category: Information Technology 

Job Level: Individual Contributor

Business Unit: Strategy & Growth

Work Type: Hybrid

Job Location: Oakland

Department Overview

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.  

Position Summary

Supports the design, development, and maintenance of data pipelines and processes used to extract, transform, and deliver reliability data from a variety of sources. Assists in implementing data transformation logic and ensuring data is properly structured and accessible for stakeholder use. Helps document metadata, including data lineage and transformation rules, to support transparency and auditability.

Contributes to the System Performance, Reliability and Resiliency Strategy team by supporting the development and curation of reliability data used in PG&E’s Electric Reliability Strategy and initiatives. Assists in maintaining data quality and ensuring data pipelines align with established governance and audit standards.

Collaborates with team members, data owners, and stakeholders to support project execution, resolve data issues, and improve data processes over time. Participates in the analytics lifecycle and develops foundational skills across data engineering, analysis, and continuous improvement practices.

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. 

PG&E is providing the salary range that the company, in good faith, believes it may pay for this position at the time of the job posting. This compensation range is specific to the job's locality.  The actual salary paid to an individual will be based on multiple factors, including, but not limited to, particular skills, education, licenses or certifications, experience, market value, geographic location, collective bargaining agreements, and internal equity. Although we estimate the successful candidate hired for this role will be placed toward the middle or entry point of the range, the decision will be made on a case-by-case basis based on these factors. This job can also participate in PG&E’s discretionary incentive compensation programs.

The hourly rate for this position ranges from $37.50 to $59.62.

Job Responsibilities

•    Assembles large, complex sets of data that meet non-functional and functional business requirements. 
•    Builds high-performance data pipelines and prototypes that enable business use of the data. 
•    Builds infrastructure for optimal extraction, transformation, and loading of data from various data sources.  
•    Understands business requirements and applies them to complex software engineering and analysis. 
•    Communicates (oral and written) recommendations with peers inside the department.  
•    Partners with team members to understand and incorporate standards information and requirements into work procedures.  
•    Identifies and analyzes departmental standards, norms, and new goals/objectives. 
•    Assists in data, design, product, and executive teams with data-related technical issues.  
•    Understands the infrastructure that allows big data to be accessed and analyzed. 
•    Utilizes department standard issue tracking, source control, and documentation tools.

Qualifications

Minimum:

•    BA/BS in Computer Science, Management Information Systems, or related field of study, or equivalent experience.

Desired:

•    1 year of experience with data engineering/ETL ecosystem, such as Palantir Foundry, Spark, Informatica, SAP BODS, or OBIEE.
•    Experience with data engineering and data transformations via a training or apprenticeship program is acceptable. 

Knowledge, Skills, Abilities, and Competencies: 
•    Business Intelligence and data access tool knowledge. 
•    Knowledge of software engineering principles such as unit testing, CI/CD, and source control.