Senior Data Engineer

General Motors (GM)

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Austin, TX
Posted: 29 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $172k

$124k most similar roles pay here $220k

This listing doesn't post a salary. Most similar roles pay $133,774–$211,200.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 116 open roles on FindRole.

Listed pay typically runs $160,200–$245,000 across 59 roles with salary data.

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At a glance

TL;DR · Senior Data Engineer

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Sr. Data Engineer - GM Motorsports The Sr. Data Engineer joins the Motorsports Data Engineering team to build next-generation data platforms for high-performance racing programs including Formula 1 and NASCAR. This role involves designing, building, and operating scalable real-time and batch data pipelines that ingest high-frequency telemetry, simulation, wind tunnel, and trackside data into an enterprise platform. The engineer will own critical components of Kafka/Flink streaming architecture, Databricks lakehouse implementations, and infrastructure-as-code deployments to enable faster, data-driven decisions for race teams. Key responsibilities include developing pipelines using Python, Java, and SQL, performing performance tuning, and mentoring fellow developers. Required technical skills include experience with AWS or Azure cloud infrastructure, Docker/Kubernetes containerization, and NoSQL databases like MongoDB and Redis. The role addresses the specific challenge of delivering high-performance data for racing analytics and telemetry systems.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

See salary data

Skills

Python Java SQL Kafka Flink Databricks AWS Azure Docker Kubernetes Mongo DB Redis REST gRPC web sockets Agile

What you'll do

Design and operate scalable real-time and batch data pipelines for high-frequency telemetry and racing data.
Manage Kafka/Flink streaming architectures and Databricks lakehouse implementations.
Develop data processing solutions using Python, Java, and SQL to solve specific business problems.
Deploy and maintain containerized applications using Docker and Kubernetes on AWS or Azure cloud infrastructure.
Automate unit and end-to-end testing of software systems to ensure quality and maintainability.
Perform performance tuning, usability assessments, and documentation for high-performance data delivery.
Provide technical guidance and mentoring to fellow software developers.
Implement infrastructure-as-code deployments to support resilient and secure data environments.

What we're looking for

Minimum 5 years of professional software development experience.
Proficiency in Python and/or Java.
Experience with event streaming or message broker technologies like Kafka, Event Hubs, or Confluent.
Experience with AWS and/or Azure cloud infrastructure.
Experience deploying and maintaining containerized applications using Docker or Kubernetes.
Experience with SQL and NoSQL database technologies such as Postgres, MongoDB, and Redis.
Experience with networking and client-server communication including REST, web sockets, gRPC, and server-sent events.
Bachelor's degree in computer science or a similar discipline.

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