Ofertas › General Motors
General Motors · Austin, TX
Description This role is categorized as hybrid. This means the successful candidate is expected to report to Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role The GM Energy Data Engineering team is on the lookout for a talented Data Engineer who is a highly skilled and hands-on Cloud Data Warehouse engineer with experience in IoT data integration, Snowflake, Databricks, and Apache Flink. The selected candidate will play a pivotal role in designing, implementing, and optimizing scalable cloud-based data warehouse solutions, including an Operational Data Store (ODS) to serve as a speed layer for advanced analytics and business intelligence initiatives. What You'll Do Develop cloud data warehouse solutions leveraging Databricks and Kubernetes. Implement robust data pipelines to ingest, process, and store IoT data from diverse sources. Integrate and manage large-scale datasets using Apache Iceberg for efficient, reliable, and scalable data lake operations. Build an Operational Data Store (ODS) to function as a speed layer, enabling rapid access for near real-time use Cases. Collaborate with data engineers, analysts, and business stakeholders to understand requirements and deliver scalable solutions. Optimize data models, storage, and compute resources for performance and cost efficiency. Ensure data quality, security, and compliance across all cloud data platforms. Setting up monitoring tools and dashboards to track pipeline health, diagnose issues, and optimize performance. Stay current with industry trends and best practices in data management, ODS technologies, and API development. Your Skills & Abilities (Required Qualifications) Bachelor's in software engineering, Computer Science, Information Technology, or a related field or equivalent experience. 7+ years experience designing, developing, and supporting enterprise applications. Proven in implementing cloud data warehouses using Databricks, Snowflake or any other data platform. Hands-on experience with Apache Flink or Spark for data lake pipelines. Experience designing and building Operational Data Stores (ODS) as speed layers for analytic environments. Experience with IoT data ingestion, processing, and analytics. Strong proficiency in SQL, Python, Java and ETL tools. Proven cloud experience and strong familiarity with at least one cloud platform (Microsoft Azure - preferred, AWS, GCP). Experienced in proactive issu