Data Engineer, Battery Data Platform & AI

Apple • Cupertino, CA

1d

About The Position

This role is on Apple's Battery Engineering team, focusing on building the data systems and AI interface that battery engineers across the company rely on. The position involves creating reliable data pipelines for a large and clean battery dataset, and developing a natural language interface to change how engineers interact with this data. The work directly impacts products used by millions of people.

The data engineer will build a platform across two main areas. Firstly, they will expand the Battery Data Warehouse (BDW), which contains data spanning the entire battery product development lifecycle, including raw materials, fabrication, testing, simulation, qualification, manufacturing, and field telemetry. This involves building reliable pipelines to ingest structured, semi-structured, and unstructured data from various global systems. A significant part of this responsibility includes building trust with source-system owners, identifying integration opportunities, and establishing Service Level Agreements (SLAs) to ensure BDW dependability.

Secondly, the role involves developing BARD, a natural language interface for the BDW. The goal is to transform how battery engineers access and analyze data, moving beyond traditional dashboards and SQL to conversational interaction, complemented by on-demand charting for real-time analysis and data exploration. This is envisioned as providing each engineer with a personal data scientist. The engineer will be responsible for the full agentic stack, including the custom MCP server, agentic search, domain knowledge integration, tool design, evaluation frameworks, and the end-to-end user experience. The position combines data engineering and AI engineering, requiring a self-directed and collaborative individual who can take ownership and drive projects forward while aligning with the team and broader company direction.

Requirements

• 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)

Nice To Haves

• MS in Computer Science, Engineering, or a related field with 0+ 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; keeping up with the latest tools, using AI daily (including for coding)
• Strong intuition for tokenization, embeddings, context engineering, eval frameworks, and MCP servers
• 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

Responsibilities

• Expand the Battery Data Warehouse (BDW) by building reliable data pipelines.
• Ingest structured, semi-structured, and unstructured data from disparate global systems into the BDW.
• Build trust with source-system owners and identify new integration opportunities.
• Establish and enforce SLAs to ensure BDW dependability.
• Build out BARD, the natural language interface to BDW.
• Engineer the full agentic stack for BARD, including MCP server, agentic search, domain knowledge, tool design, evals, and user experience.
• Drive projects forward with ownership and collaboration.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level