Job Location: San Francisco, CA
Job Location: San Francisco
Team Overview
The Decision Products team strives to utilize best in class modeling techniques and industry leading data science to drive PG&E’s transition to the sustainable energy network of the future through data driven decision making. This work moves beyond descriptive reporting and is focused on pushing the business forward through applied statistics, predictive and prescriptive analytics, and insightful tool design. The cornerstone of these high value analytics is one of the largest smart meter usage databases in the industry, that when combined with billing, program engagement, customer demographic, grid, and other data sources has unprecedented potential.
Current and past projects include:
Deployment of computer vision algorithms in tools that accelerate and automate asset inspections processes
Predicting electric distribution equipment failure before it occurs allowing for proactive maintenance
Optimizing renewable resource portfolios, including location and resource adequacy considerations
Supporting asset strategy decision making including, where should PG&E underground electrical assets
Supervised and unsupervised machine learning models using Python and Spark, trained on AWS, deployed on Palantir Foundry
Position Summary
We are looking for a savvy Data Engineer to join our growing team of analytics experts. In this role you will work as part of cross functional teams, including data scientists, other data engineers, technology experts, and subject matter experts to develop data driven solutions. Successful candidates will be responsible for building, expanding, and optimizing our data, data storage, and data pipeline. This individual will support team members and decision products to ensure that data delivery is reliable and optimized. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. facilitative leadership this role will help the team continue its history of success. Qualified candidates will have a unique opportunity to be at the forefront of the utility industry and gain a comprehensive view of the nation’s most advance smart grid. It is the perfect role for someone who would like to continue to build upon their professional experience and help advance PG&E’s sustainability goals.
Responsibilities:
Project Specific Data Engineering
Leads data engineering activities on moderate to complex data and analytics-centric problems which have broad impact and require in-depth analysis to obtain desired results.
Plans work to meet mutually agreed to objectives; reviews progress with team members regularly; documents work in a manner that is aligned with best practices
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.
Actively participates in agile/scrum ceremonies (stand ups, planning, retrospectives, etc.)
Builds and conducts automated and user acceptances tests as part of an iterative development process
Promotes a continuous improvement mindset by engaging in after action reviews and sharing learnings
Broader Data System and Architecture Maturity
Assesses performance of individual data pipeline and broader data systems, suggests and may implement changes as required to meet individual project or enterprise maturity objectives
Provides assistance to other programmers/analysts on unusual or especially complex problems that cross multiple functional/technology areas. May require creative/non-standard approaches to solve problems that will have significant impact across the company
Conceptualizes and generates infrastructure that allows big data to be accessed and analyzed with verified data quality and metadata is appropriately captured and catalogued
Work with team leadership to continually improve data driven decision making at PG&E via demonstrations, mentoring, disseminating best practices, etc.
Minimum Qualifications:
BA/BS or equivalent experience in appropriate technical discipline (Computer Science, Management Information Systems or related field of study)
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 including cloud based Dev Ops and ML Ops.
Desired Qualifications:
Proven track record of successfully implementing data warehouses/data lakes over previous five years.
Experience leading development teams
History of working on complex multi-stage projects with a diverse team
Demonstrated commitment to teamwork and enabling others
Proven ability to translate business desires into technical requirements
Experience with relevant project management tools (Jira, Asana, etc.), version control tools (Git, Bitbucket. etc.), data science and machine learning tools/infrastructure (AWS suite of products, Jupyter, etc.), and methodologies (Agile, Design thinking, Kanban, etc.)”
Involvement or strong interest in the energy/clean tech industry
Expressed interest in learning, experimentation, and incorporation of new techniques
Ability to adapt to and improve existing processes
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