Data Engineer, Expert

Pacific Gas And Electric Company•Oakland, CA

2d•$140,000 - $238,000•Hybrid

About The Position

The Data Solutions team in the Wildfire Mitigation organization aims to enhance the risk practices of PG&E’s Electric Operation business and address changing external conditions such as climate change. The team enhances and maintains predictive models of electric system failures. These models provide a multi-layered view of risk across the electric system, empowering employees at all levels to manage risk appropriately. Sample activities include the development of new Machine Learning (ML) models characterizing and predicting distribution and transmission electric system environmental conditions using geospatial data, and the development of end-to-end solutions that transform various geospatial data into analysis-ready insights and cloud-optimized datasets accessible within distributed Spark environments. The team also supports stakeholders in integrating features into downstream analysis and risk models. This position designs, develops, modifies, configures, debugs, and evaluates jobs for extracting data from various sources, implements transformation logic, and stores data in various formats fit for use by stakeholders. This role collects metadata about jobs, including data lineage and transformation logic. The Data Engineer works with teams, clients, data owners, and leadership throughout the development cycle, practicing continuous improvement. This position is hybrid, requiring work from a remote office and the assigned work location based on business need, which will be within the Bay Area of the PG&E Service Territory.

Requirements

BA/BS in Computer Science, Management Information Systems or related field of study, or equivalent experience.
7 years of experience with data engineering/ETL ecosystems 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, Data science, Engineering, or a related field, or equivalent experience.
Leadership experience, development teams
Cloud-native data platform experience
Knowledge of software engineering principals such as unit testing, CI/CD, source control.
Generative AI experience, including LLMs, RAG, and agentic workflows
Geospatial data engineering experience, including spatial analytics and satellite imagery products

Responsibilities

Leads a team on moderately complex to complex data and analytics-centric problems having 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 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.
Evaluates emerging technologies, including Generative AI solutions, to improve data engineering, analytics, and business processes.
Provides assistance to 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 catalogued.
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/provides guidance to less experienced colleagues.