Data Platform Lead - IT Transformation

Primary Responsibilities

• Partner with Solar / Wind / Thermal Operations, Performance Engineering, Asset Management, and other teams to discover and prioritize the first data use cases – contributing to stakeholder interviews, mapping current Excel-based workflows, and defining what to build first on the platform.
• Design, build, and maintain ingestion and transformation pipelines in a cloud-hosted data lake (within DataBricks, etc.) to bring operational data from AVEVA PI, Ignition, Maximo, Workday, and ISO/market sources into a governed Lakehouse — covering wind, thermal, and solar assets.
• Serve as the technical counterpart to external consulting partners engaged in the platform build, translating business requirements into pipeline specifications, validating deliverables, and ensuring work aligns with Onward's long-term architecture.
• Own long-term pipeline reliability end-to-end: define data availability and quality standards, build monitoring and alerting, and resolve ingestion or transformation failures before they impact downstream reporting.
• Contribute to data governance practices - including ownership models, role-based access for sensitive operational and financial data, and quality standards.

The Profile to Succeed

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 4+ years of hands-on data engineering experience building and operating production pipelines and data models.
• Demonstrated ability to translate ambiguous business problems into well-scoped technical work and to define structure where none exists.
• Excellent written and verbal communication skills, with the ability to engage credibly with both engineers and non-technical business stakeholders.
• Experience integrating data from heterogeneous source systems - APIs, file-based feeds, relational databases, and time-series or historian data.
• Production experience building pipelines in Python and SQL on a distributed framework.
• Experience scheduling, orchestrating, and monitoring data pipelines - whether through Airflow or similar tools.
• Experience designing and managing table structures in a Lakehouse or Warehouse environment – including incremental merge patterns, schema evolution, and partitioning strategies.
• Experience implementing or operating data governance tooling — including access controls, lineage tracking, and data cataloging — in a Lakehouse or warehouse environment.
• Experience with Unity Catalog preferred.
• Working knowledge of core Azure services in a Databricks context (storage, identity, secrets management) and ability to navigate the ecosystem independently.

PREFERRED QUALIFICATIONS

• 2+ years in management or technology consulting, demonstrating comfort with ambiguity, a business-first approach to requirements, and the ability to balance an engineering skillset with a business analyst skillset.
• Energy industry experience (generation, utilities, ISO/RTO markets) or familiarity with operational technology data such as SCADA or CMMS platforms.
• Experience with at least one greenfield or early-stage platform build (Databricks is preferred) where a focus on design / architecture was required.
• Familiarity with Power BI semantic modeling and DAX, including how to structure datasets on top of a Lakehouse for performant, self-service reporting.