About the role
What will you do at Apple?
What if the way an entire engineering organization worked with its data could be
reinvented? On Apple's Battery Engineering team, you'll 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 that's changing how engineers work with that data.
You'll be building the platform the whole battery organization runs on. It's a
rare chance to sharpen your data engineering craft and immerse yourself in
applied AI at once — on a mission where your work shows up in the products
millions of people use every day.
DESCRIPTION
We're looking for a senior data engineer to build that platform across two
tightly connected fronts. First, you'll 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. You'll 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
dependable. Second, you'll 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. You'll engineer the full agentic stack: our custom MCP server,
agentic search, domain knowledge, tool design, evals, and the end-to-end user
experience. The role combines data engineering and AI engineering work, and it's
a senior individual-contributor position on the Battery Data Engineering team.
This role calls for someone who's both highly self-directed and an exceptional
collaborator. You'll take real ownership and drive projects forward, while
staying closely aligned with the team and our broader direction.
MINIMUM QUALIFICATIONS
BS in Computer Science, Engineering, or a related field Experience with Python,
SQL, and at least one other high-level programming language Experience building
production data pipelines (ETL/ELT)
PREFERRED QUALIFICATIONS
MS in Computer Science, Engineering, or a related field with 3+ years of
relevant industry experience Software engineering background and strong database
fundamentals: data modeling, schema design, indexing, normalization, ACID, and
OLTP vs. OLAP Hands-on database development (DML, DDL, materialized views,
stored procedures); Snowflake (streams, tasks, dynamic tables) a plus Hands-on
experience with orchestration (e.g., Airflow), batch/stream processing, and
cloud platforms (e.g., AWS) Deep curiosity about AI and hands-on experience
applying it; you keep up with the latest tools, use AI daily (including for
coding), and have strong intuition for tokenization, embeddings, context
engineering, eval frameworks, and MCP servers, as well as a clear sense of where
AI excels and where it doesn't (e.g., generating new code vs. maintaining
complex existing code) Experience securing AI/LLM systems that process sensitive
or regulated data, including prompt injection defense, data handling policies,
and audit trail requirements Excellent written and verbal communication skills
with both technical and non-technical audiences Familiarity with batteries or
other deep-tech / hardware engineering domains
Which skills does this role require?
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