Forward Deployed Data Engineer IV, Databricks

🕒 September 16

🇺🇸 United States – Remote

💵 $175k - $200k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 0%

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E Source

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1986

⚡ Energy

💼 Consulting

🤝 B2B

Energy • Consulting • B2B

E Source is a research, data-science, and consulting firm that helps electric, gas, and water utilities make and implement data-driven decisions. The company combines industry-leading research, benchmarking, consulting services, and applied analytics (including machine learning and AI support) to improve customer experience, optimize grid operations, modernize business and field processes, and design and evaluate energy programs. E Source offers solutions across customer operations, DER strategy and measurement, AMI planning and implementation, vegetation/storm/wildfire/reliability intelligence, interconnection studies, data strategy and governance, and workforce and technology transformation. It serves utilities across North America and emphasizes linking strategy to execution for measurable operational and customer outcomes.

📋 Description

• Embed with utility clients to design and build production data platforms end to end • Build ingestion, transformation, orchestration, quality, governance, and serving systems using Databricks, Spark, Python, SQL, and AWS • Own technical architecture for each engagement and defend it to client architects, security teams, and platform owners • Conduct independent technical discovery and identify underlying client needs • Deliver a working system within the first few weeks and iterate toward production hardening • Lead migrations from legacy warehouses and on-premises systems to modern platforms • Model data using dimensional, lakehouse/medallion, graph, or semantic models as appropriate • Integrate utility source systems including asset and work management, historians/SCADA, CIS, AMI, GIS, and ERP • Make pipelines observable and operable through lineage, quality checks, alerting, and runbooks • Build and deploy operator-facing application layers such as data quality dashboards, reconciliation interfaces, and self-service data tools • Manage scope, timeline, expectations, risks, and measurable outcomes against statements of work • Contribute reusable frameworks, ingestion patterns, and reference architectures • Provide product and implementation feedback to E Source engineering and product teams • Apply governance, security, privacy, and retention controls appropriate to utility regulations • Work with client data/IT teams, executives, and E Source ML engineers, software engineers, data scientists, and consultants • Travel to client sites approximately 30–50%, varying by engagement, including extended on-site periods

🎯 Requirements

• Bachelor’s degree in computer science, information technology, or a related field • Five or more years of experience in data engineering, data platform, or analytics engineering • At least one platform owned in production • Expert proficiency in Python, SQL, Databricks, and Spark, including Spark runtime internals • Ability to diagnose why a Spark job is slow rather than simply adding compute • Experience building cloud-based data pipelines in AWS • Working knowledge of a second cloud ecosystem preferred • Experience with incremental versus full rebuild, idempotency, late-arriving data, deduplication, backfill strategy, and schema evolution • Batch and streaming pipeline design experience • Knowledge of data governance, security, privacy, lineage, and quality practices • Proficiency with Git, Docker, CI/CD tools, and at least one modern orchestration framework • Demonstrated experience using AI coding assistants and agentic development tools • Experience in the energy or utility industry, or another asset-heavy sector • Strong written communication and whiteboarding skills • Master’s degree in a relevant STEM field preferred • Graph database and knowledge graph modeling experience preferred • Production experience with Kafka or equivalent streaming platforms and change data capture tooling preferred • Experience building feature pipelines and serving data to ML and AI systems preferred • Experience building and deploying Databricks Apps or comparable operator-facing applications preferred • Experience with React, Streamlit, or Dash and REST or GraphQL APIs preferred • Experience optimizing Databricks cost and performance preferred • Databricks certification preferred • Applicants must be authorized to work for any employer in the US • Employment visa sponsorship is unavailable

🏖️ Benefits

• Excellent insurance options, including medical, dental, and vision plans • Company-paid life insurance • Company-paid long- and short-term disability insurance • Medical and dependent-care flexible spending plans • Paid parental leave • Flexible time off (FTO) policy • 401(k) plan with a 3% employer match • Annual bonus • Remote-based work within the US • Significant travel to client sites, including extended on-site periods during discovery, deployment, and go-live