Job Description
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Company Overview
A leading global technology company is advancing the future of battery engineering through innovative data platforms and AI-powered solutions. The organization is focused on building large-scale, high-quality battery datasets and intelligent tools that empower engineers to make faster, data-driven decisions throughout the battery product development lifecycle. By combining robust data infrastructure with cutting-edge AI capabilities, the company supports the development of products used by millions of people worldwide.
The organization is seeking a Data Engineer, Battery Data Platform & AI to help build and scale a critical data ecosystem supporting battery engineering teams. This role combines data engineering and AI engineering, offering the opportunity to work on both enterprise-grade data platforms and advanced natural language interfaces that transform how engineers interact with data.
The successful candidate will play a key role in expanding a mature battery data warehouse while also developing AI-powered tools that enable engineers to explore and analyze data through natural language. This position requires a highly self-directed individual who can drive projects independently while collaborating effectively across cross-functional teams.
Key Responsibilities
- Partner with cross-functional and engineering teams to identify data opportunities, define domain ontologies, and establish use cases that drive the battery data platform.
- Design, build, and maintain production-grade ETL/ELT pipelines that ingest structured, semi-structured, and unstructured data from multiple systems.
- Develop relationships with source-system owners to unlock new data integrations and ensure reliable data delivery through defined SLAs.
- Engineer and enhance a natural language interface for the battery data warehouse, including agentic search, domain knowledge integration, tool design, evaluation frameworks, and end-to-end user experiences.
- Collaborate with infrastructure, database, and IT teams to maintain the health and performance of data pipelines and warehouse systems.
- Apply AI technologies to improve engineering workflows and solve complex business challenges.
- Develop and deliver data analyses that support critical decisions across battery research, development, testing, manufacturing, and qualification processes.
- Contribute to the design and implementation of AI systems that enable conversational access to engineering data and real-time analytical insights.
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 principles and large-scale data management.
Preferred Qualifications
- Master’s degree in Computer Science, Engineering, or a related field with 3+ years of relevant industry experience.
- Strong software engineering background and 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 technologies, including streams, tasks, and dynamic tables.
- Experience with orchestration platforms such as Airflow, batch and stream processing systems, and cloud environments such as AWS.
- Deep interest in AI and practical experience applying AI technologies, including tokenization, embeddings, context engineering, evaluation frameworks, and MCP servers.
- Understanding of AI strengths, limitations, and best practices for software development and data applications.
- Experience securing AI and LLM systems that process sensitive or regulated data, including prompt injection mitigation, data governance, and audit requirements.
- Excellent written and verbal communication skills with both technical and non-technical stakeholders.
- Familiarity with battery technologies or other deep-tech and hardware engineering domains.
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