Data Engineer — EV Battery Analytics Platform

James Okafor

Contract-to-hire · Mid-level · Seoul

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About the role

We are the data engineering division of a South Korean electric vehicle battery manufacturer. Our parent company produces battery cells and pack systems for passenger vehicles, commercial trucks, and energy storage applications. We supply six automotive OEM customers across Korea, the United States, Germany, and Japan. The data engineering team is based in Seoul with remote members in the US and Germany. We are hiring English-speaking data engineers — this team works in English and the role is fully remote. Battery cells generate continuous telemetry from manufacture through deployment in the field. A single production batch of cells goes through fourteen measurement stations before it ships. Once deployed in a vehicle, the battery management system sends state-of-charge, temperature, impedance, and cycle count data back to us continuously across the vehicle's lifetime. The analytical challenge is significant: relating manufacturing process parameters to field performance outcomes, detecting early indicators of capacity degradation, and building the data infrastructure that our battery development and quality engineering teams use to make decisions. We are hiring a mid-level data engineer on a six-month contract with the intention — strongly held — of converting to a permanent role if the technical fit and collaboration work well.

Responsibilities

Build and maintain the real-time ingestion pipeline from vehicle battery management systems to our analytics data warehouse
Design the manufacturing-to-field data linkage: connecting cell production lot records to field performance outcomes for the battery development team
Implement data quality validation for manufacturing measurement data — detecting sensor drift, measurement outliers, and process anomalies
Contribute to the design of the time-series data model for battery performance analytics at scale
Document pipelines, data models, and operational procedures to the standard required for handoff to new team members as the team grows

Requirements

4+ years of data engineering with experience building production pipelines on high-volume, structured time-series industrial data
Apache Spark for distributed processing of large-scale telemetry datasets from manufacturing and field operations
Kafka for real-time ingestion of battery management system telemetry from vehicle fleets
Python for pipeline development, data transformation, and tooling at a professional standard
SQL for working with manufacturing quality databases, cell test records, and field performance data warehouses
GCP — BigQuery and Dataflow — our primary cloud platform for batch and streaming workloads
Experience with IoT or industrial telemetry data — time-series alignment, sensor drift, missing data, and the practical challenges of data from physical systems

Benefits

$110,000 – $132,000 annualised contract rate — permanent salary to be discussed at conversion
6-month initial contract with strong intention to convert
Fully remote — team is distributed across Seoul, San Francisco, and Munich
Annual learning budget of $2,000
Work at the intersection of battery technology and data infrastructure — the problem is technically interesting and commercially significant