General Motors Manufacturing is looking to improve decisions, plant asset maintenance, safety, and operational performance by leveraging plant floor data through the development of real-time solutions.
Requirements
- 7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL)
- 3+ years of experience in distributed data processing (Spark) and container orchestration (Kubernetes)
- Proficiency in data streaming in Kubernetes and Kafka
- Experience with cloud platforms – Azure preferred; AWS or GCP also considered.
- Solid understanding of CI/CD principles and tools
- Familiarity with big data technologies such as Hadoop, Hive, HBase, Object Storage (ADLS/S3), Event Queues.
- Strong understanding of performance optimization techniques such as partitioning, clustering, and caching
Responsibilities
- Assemble large, complex data sets that meet functional and non-functional business requirements.
- Identify, design, and implement process improvements, including automation, data delivery optimization, and infrastructure redesign for scalability.
- Lead and deliver data-driven solutions across multiple languages, tools, and technologies.
- Contribute to architecture discussions, solution design, and strategic technology adoption.
- Build and optimize highly scalable data pipelines incorporating complex transformations and efficient code.
- Design and develop new source system integrations from varied formats (files, database extracts, APIs).
- Design and implement solutions for delivering data that meets SLA requirements.
Other
- This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI or Austin, TX three times per week, at minimum
- GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE.
- Strong collaboration and communication skills; ability to work across multiple teams and disciplines.
- Mentor peers and junior engineers; educate colleagues on emerging industry trends and technologies.
- The expected base compensation for this role is: $134,000 - $219,400.
