Jobs at E Source

Lead product strategy and roadmap for Storm Insights; own backlog and translate priorities into epics, features, and user stories; collaborate with engineers, data scientists, and designers; run agile ceremonies; validate releases and coordinate UAT; synthesize client feedback and utility operational data to improve storm readiness and restoration workflows.

Design, build, and maintain scalable data pipelines, lakes, and infrastructure using Databricks, Spark, Python, and AWS. Collaborate with ML engineers, data scientists, and analysts to deliver data products, ensure data quality and governance, implement DevOps/SDLC practices, mentor junior engineers, and evaluate new data technologies.

Design and build secure, scalable cloud-native, AI-enabled applications and microservices for utilities. Lead architecture, translate requirements, develop APIs and data-driven solutions, mentor engineers, and ensure software quality and delivery.

Lead and grow an interconnection team delivering transmission and distribution capacity analysis, interconnection application support, model development and ISO/TO study review. Provide technical guidance and client-facing leadership across major ISOs/RTOs, support owners engineering and market analysis, and drive business development and market engagement.

Own and evolve the lead-to-invoice enterprise application stack (NetSuite, Salesforce, Marketo, PSA, HR systems). Design and govern integrations, maintain architecture maps, lead integration projects, manage vendors, ensure testing and documentation, partner with business leaders, and pilot AI-enabled features to drive automation and adoption.

Serve as an in-house expert on DER and grid-edge topics, conduct primary and secondary research, synthesize findings into clear written and presented deliverables, engage with utility clients, mentor junior analysts, and support advisory projects and industry representation.

Design, build, and deploy scalable AI/ML systems and pipelines. Develop reusable Python packages, RAG/LLM integrations, agentic workflows, evaluation/monitoring frameworks, optimized data queries, and MLOps practices while collaborating across cross-functional teams.

Support the Data Analyst team by updating data tools, conducting research, organizing and analyzing quantitative and qualitative utility data, documenting workflows, and translating findings into written and visual summaries for clients and internal teams.