Technical Lead, Data Engineering

Reporting to the Head of Information Technology, the Technical Lead, Data Engineering owns Proterra’s data platform end to end: the pipelines that land Oracle E-Business Suite, manufacturing, PLM, and telemetry data in the AWS Data Lakehouse, and the Power BI and Battery360 consumption layer the business uses every day.

This is the senior technical role on a deliberately lean Data team. The position is accountable both for the engineering underneath and for what the business actually sees, sets the technical standards the platform is built to, carries the platform’s most consequential sequencing decisions, and serves as the technical partner to Manufacturing, Quality, Supply Chain, and Product.

About the Role – You will:

• Own the design, build, and operation of the AWS Data Lakehouse and the pipelines that feed it from Oracle E-Business Suite, Ignition, Visual Factory, 3DX, and warranty telemetry.
• Deliver the consumption layer the business runs on: Clear to Build, Quality dashboards, Item Master, PPAP, SPI, and production control reporting in Power BI.
• Sequence the data pipeline against the Oracle E-Business Suite upgrade and cloud migration so analytics feeds survive the cutover, including regression testing of the analytics feeds and not only the ERP transactions.
• Rebuild the telemetry and warranty data layer following the Palantir exit, re-establishing the pack serial number to VIN relationship that warranty depends on, and deliver the replacement front end through Battery360.
• Prepare the data foundation for the EU Digital Battery Passport: material, bill of material, responsible sourcing, and state of health data assembled from governed Lakehouse sources.
• Set and enforce technical standards and best practices for ingestion, transformation, data modeling, data quality, and governance; lead code and design reviews.
• Document pipelines, models, and runbooks as they are built so that no workstream depends on a single person.
• Partner with stakeholders in Manufacturing, Quality, Supply Chain, and Product to turn business questions into reliable, well modeled data products.
• Implement monitoring, automation, and CI/CD for data pipelines, and own the cost, performance, and reliability of the platform on AWS.
• Build the data foundation for analytics and AI use cases on the Lakehouse, beginning with predictive maintenance, operating within Proterra’s AI governance policy (CYB-POL-009).
• Ensure data security, privacy, and compliance within the data platform.
• Provide technical leadership and mentorship to data and analytics staff.