Technical Lead, Data Engineering

Proterra•Greer, SC

18h•Onsite

About The Position

Proterra offers a dynamic and supportive workplace where our employees can thrive personally and professionally. With cutting-edge facilities and groundbreaking projects, Proterra offers unique opportunities to grow, collaborate, and lead transformative change in the electrification of heavy-duty transportation and equipment. Our commitment to innovation extends beyond our battery solutions to our people, where we create an environment where everyone feels valued, supported, and empowered to drive change for the earth. Here at Proterra we strive to foster a culture of inclusivity, valuing diverse perspectives and encouraging bold ideas, allowing our employees to bring their full selves to work. Our employees benefit from competitive total rewards packages, and opportunities to develop professionally. 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.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, a related field, or equivalent work experience.
Generally requires a minimum of 6 to 8+ years in data engineering, including technical leadership of a platform or a team.
Demonstrated ownership of a production cloud data platform, not pipeline development alone.
Experience integrating ERP and manufacturing execution data. Oracle E-Business Suite and a shop floor system such as Ignition are strongly preferred.
Experience delivering business-facing analytics and dashboards, not only upstream pipelines.
SQL and Python for production data engineering.
AWS data services and pipeline orchestration.
ETL / ELT design and dimensional data modeling.
Power BI semantic modeling and report delivery.
CI/CD, infrastructure as code, and automation for data pipelines.
Data quality, security, lineage, and governance.
Technical leadership, mentorship, and documentation discipline.
Ability to work directly with manufacturing, quality, and supply chain stakeholders and translate between business need and technical design.

Nice To Haves

AWS data or analytics certification (AWS Certified Data Engineer, AWS Certified Solutions Architect) preferred, since AWS is the platform in use.
Microsoft Power BI certification.
Databricks, Snowflake, or Azure credentials are considered transferable experience rather than a match to the current platform.

Responsibilities

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.