Data Engineer – Battery Data Platform & AI

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Company Overview

A leading global technology company is advancing the future of battery engineering through data-driven innovation and artificial intelligence. The organization is building a sophisticated Battery Data Platform that supports the entire battery product development lifecycle, from raw materials and manufacturing to field telemetry and performance analysis. By combining large-scale data infrastructure with AI-powered interfaces, the company is transforming how engineers access, analyze, and interact with critical battery data.

The organization is seeking a Data Engineer – Battery Data Platform & AI to help build and expand a world-class battery data ecosystem. This role combines data engineering and AI engineering responsibilities, offering the opportunity to develop reliable data infrastructure while creating advanced natural language interfaces that redefine how engineering teams interact with data.

The successful candidate will work across two key initiatives: expanding a comprehensive Battery Data Warehouse that consolidates structured, semi-structured, and unstructured data from global systems, and enhancing an AI-powered natural language platform that enables engineers to explore and analyze battery data through conversational interactions. This position requires a highly self-directed individual who can drive technical projects while collaborating effectively with stakeholders across multiple teams.

Key Responsibilities

• Partner with cross-functional and engineering teams to identify data opportunities, define domain ontology, and establish use cases that drive the Battery Data Warehouse.
• Design, build, and maintain production-grade ETL/ELT data pipelines that ingest structured, semi-structured, and unstructured data from multiple sources.
• Build strong relationships with upstream source-system owners to unlock new integration opportunities and establish reliable pipeline SLAs.
• Engineer and enhance the natural language interface to the Battery Data Warehouse, including agentic search capabilities, MCP server architecture, domain knowledge integration, tool design, evaluation frameworks, and user experience.
• Collaborate with infrastructure, database, and IT teams to ensure the health, scalability, and reliability of data pipelines and warehouse systems.
• Apply AI technologies to improve engineering workflows and solve complex battery engineering challenges.
• Deliver data analyses and insights that support critical decisions in battery research, development, testing, and qualification.
• Drive innovation in data accessibility through conversational AI and advanced analytics capabilities.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience with Python, SQL, and at least one additional high-level programming language.
• Proven experience building and maintaining production data pipelines (ETL/ELT).
• Strong understanding of data engineering best practices and large-scale data integration.

Preferred Qualifications

• Master’s degree in Computer Science, Engineering, or a related field.
• 10+ years of relevant industry experience.
• Strong database fundamentals, including data modeling, schema design, indexing, normalization, ACID principles, and OLTP versus OLAP architectures.
• Hands-on experience with database development, including DML, DDL, materialized views, and stored procedures.
• Experience with Snowflake, including streams, tasks, and dynamic tables.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of batch and stream processing systems.
• Experience working with cloud platforms such as AWS.
• Deep interest in AI with hands-on experience applying AI tools and technologies in professional or personal projects.
• Strong understanding of context engineering, tokenization, embeddings, evaluation frameworks, and practical AI implementation.
• Experience developing applications using Large Language Models (LLMs) and MCP servers.
• Excellent communication and stakeholder management skills with the ability to drive collaboration across organizational boundaries.
• Familiarity with battery technologies, hardware engineering, or other deep-tech domains.

Disclaimer

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