Requisition ID # #

Job Category:

Information Technology Job Level:

Individual Contributor Business Unit:

Energy Delivery Work Type:

Hybrid Job Location:

Oakland Department Overview The aim of the Data Solutions team in the Wildfire Mitigation organization is to enhance the risk practices of PG&E's Electric Operation business and thereby address changing external conditions such as climate change. To this end the Data Solutions team enhances and maintains predictive models of electric system failures. These models help to provide a multi-layered view of risk across the electric system so that decision-making processes include and empower employees at all levels of the company to manage risk appropriately.

Sample activities include:

• Development of new Machine Learning (ML) models characterizing and predicting distribution and transmission electric system environmental conditions using geospatial data.
• Development of end-to-end solutions that takes a variety of geospatial data and transform them into analysis-ready insights, cloud optimized datasets accessible within distributed Spark environments.
• Support for stakeholders in how to integrate features into downstream analysis and risk models.

Position Summary 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. Collects metadata about jobs including data lineage and transformation logic. Works with teams, clients, data owners, and leadership throughout the development cycle practicing continuous improvement. This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the Bay Area of the PG&E Service Territory. PG&E is providing the salary range that the company in good faith believes it might pay for this position at the time of the job posting. This compensation range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, specific skills, education, licenses or certifications, experience, market value, geographic location, and internal equity. Although we estimate the successful candidate hired into this role will be placed towards the middle or entry point of the range, the decision will be made on a case-by-case basis related to these factors.

Bay Minimum:

# ,000

Bay Maximum:

# ,000 This job is also eligible to participate in PG&E's discretionary incentive compensation programs. Job 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.

Qualifications Minimum:

• 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.

Desired:

• 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