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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** General Motors - **Location:** Warren, MI, United States - **Experience:** Expert - **Salary:** $125,000.0 - $168,650.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Software as a Service, Cloud Computing, Cluster Analysis, Databases, Continuous Delivery, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Normalization, Data Systems, Relational Databases, Distributed Computing Environment, Apache Hadoop, Apache HBase, Apache Hive, Python (Programming Language), Meta-Data Management, SQL Azure, NoSQL, Performance Tuning, Cloud Services, Azure Data Lake, Simple Data Format, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Azure Service Bus, Snowflake, Apache Spark, Caching, Data Lakes, Kubernetes, Information Technology, Production Code, Data Analytics, Apache Kafka, Azure AKS, Video Streaming, Data Delivery, Data Pipelines, Databricks - **Published:** October 14, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3445763045&tx=FJ3532FFP&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience * 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 * Proven experience with Fivetran (pipeline setup, connectors, transformations) * 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 * Proficiency with SQL, key-value datastores, and document stores * Familiarity with data architecture and modeling concepts to support efficient data consumption * Advanced understanding of data normalization and denormalization techniques. * Translate enterprise requirements into effective data models and address project requirements when applicable. * Design, build, and optimize scalable batch and streaming data pipelines using Databricks (Apache Spark, Delta Lake) to support Medalion Architecture. * Automate workflows and maintain clear documentation for all data processes. * Contribute to the design and operational management of a cloud-native data platform on Azure , integrating services such as Azure Data Lake Storage, Event Hubs, Azure SQL, and AKS. * Monitor and troubleshoot data pipelines and platform workloads. Optimize Spark jobs, cluster configurations, and SQL warehouses to improve performance * Strong collaboration and communication skills; ability to work across multiple teams and disciplines. What Can Give You a Competitive Advantage (Preferred Qualifications) * Master's degree in Computer Science, Software Engineering, or related field * Knowledge of data governance, metadata management, or data quality/observability * Familiarity with schema design and data contracts * Experience handling various file formats (video, audio, image) * Experience with Databricks, Snowflake, or similar platforms ## Description This role is categorized as hybrid. This means the successful candidate is expected to report to Austin Technical Center in Austin, TX or GM Global Tech Center in Michigan, MI three times per week, at minimum [or other frequency dictated by the business if more than 3 days]., As a Data Engineer with Fivetran tool focus, you will design, build, and optimize industrialized data assets and data pipelines in support of Business Intelligence and Advanced Analytics objectives. In this role within the Intelligent Manufacturing organization under Data Engineering Software, you will deliver high-quality, scalable solutions that meet both functional and non-functional business requirements. You will contribute to projects across databases, streaming technology, CI/CD, and cloud platforms. The Intelligent Manufacturing teams are responsible for ideating, incubating, and delivering new plant data solutions for General Motors Manufacturing and our partners. We integrate with business and IT teams to develop real-time solutions that leverage plant floor data to improve decisions, plant asset maintenance, safety, and operational performance, as well as Vehicle Build Data. This is a senior-level role that blends strong data engineering skills with modern software engineering practices. You will help lead and deliver innovative, scalable, and maintainable data-driven solutions-writing high-quality, tested, production-ready code that meets customer needs and scales without rework. You will work in a collaborative, cross-disciplinary environment, handle complex challenges, contribute to architectural discussions, and help shape solutions that improve performance, scalability, and maintainability, while also ensuring alignment with business priorities. What You'll Do * 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. * Develop and configure end-to-end data pipelines using Fivetran, ensuring efficient extraction, transformation, and loading (ETL) processes.Integration Setup: Connect multiple data sources (APIs, SaaS platforms, databases) to Fivetran and manage schema mapping and transformations. * Monitor pipeline performance, troubleshoot issues, and implement improvements for scalability and reliability. * 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. * Work with operations teams to resolve production issues related to the platform. * Apply best practices such as Agile methodologies, design thinking, and continuous deployment. * Develop tooling and automation to make deployments and production monitoring more repeatable. * Collaborate with business and technology partners, providing leadership, best practices, and coaching. * Mentor peers and junior engineers; educate colleagues on emerging industry trends and technologies.