Data Engineer Battery Data Platform & AI

What if the way an entire engineering organization worked with its data could be reinvented On Apples Battery Engineering team youll build the data systems and AI interface that battery engineers across the company rely on reliable pipelines feeding one of the cleanest and largest battery datasets anywhere and a natural language interface thats changing how engineers work with that data. Youll be building the platform the whole battery organization runs on. Its a rare chance to sharpen your data engineering craft and immerse yourself in applied AI at once.

Were looking for a data engineer to build that platform across two tightly connected youll expand the Battery Data Warehouse (BDW) a mature exceptionally clean dataset that spans the entire battery product development lifecycle: raw materials and characterization fabrication performance testing simulation and modeling qualification manufacturing and field telemetry. Youll build reliable pipelines that bring this data - structured semi-structured and unstructured - out of disparate systems owned by teams around the world. A big part of the job is technical; an equally big part is human: earning the trust of source-system owners opening up new integration opportunities and establishing and enforcing the SLAs that keep BDW youll build out BARD the natural language interface to BDW. Done well BARD will fundamentally change how battery engineers interact with their data not just replacing dashboards and SQL with conversation but pairing it with on-demand in-line charting for real-time analysis and new ways to explore data. Think of it as giving every engineer their own personal data scientist. Youll engineer the full agentic stack: our custom MCP server agentic search domain knowledge tool design evals and the end-to-end user role combines data engineering and AI engineering work. This role calls for someone whos both highly self-directed and an exceptional collaborator. Youll take real ownership and drive projects forward while staying closely aligned with the team and our broader direction.

Partner with cross-functional and engineering teams to identify data opportunities define domain ontology and establish the use cases that drive BDWnDesign build and maintain production data pipelines (ETL/ELT) that bring structured semi-structured and unstructured data into BDW at the right cadence and reliabilitynBuild relationships with upstream source-system owners to unlock new data integrations and establish and enforce pipeline SLAsnEngineer BARD the natural language interface to BDW designing the agentic stack (MCP server agentic search domain knowledge tool design evals) and its end-to-end user experiencenPartner with infrastructure teams (DBA IT) to ensure the health of pipelines and the data warehousenApply AI to your own workflow and to the battery organizations problems bringing strong intuition for context engineering embeddings tokenization and evalsnDeliver data analyses that drive critical decisions in battery research development and qualification

BS in Computer Science Engineering or a related fieldnExperience with Python SQL and at least one other high-level programming languagenExperience building production data pipelines (ETL/ELT)

MS in Computer Science Engineering or a related field with 10 years of relevant industry experiencenStrong database fundamentals: data modeling schema design indexing normalization ACID and OLTP vs. OLAPnHands-on database development (DML DDL materialized views stored procedures); Snowflake (streams tasks dynamic tables) a plusnHands-on experience with orchestration (e.g. Airflow) batch/stream processing and cloud platforms (e.g. AWS)nDeep curiosity about AI and hands-on experience applying it at work or in personal projects. You keep up with the latest tools use AI daily (including for coding) and have strong intuition for context engineering tokenization embeddings and evals as well as a clear sense of where AI excels and where it doesnt (e.g. generating new code vs. maintaining complex existing code)nExperience with LLM and MCP server developmentnStrong communication and relationship-building skills with the ability to align stakeholders and drive integrations across organizational boundariesnFamiliarity with batteries or other deep-tech / hardware engineering domains