This role is categorized as hybrid. This means the successful candidate is expected to report to offices in Austin, TX, Mountain View, CA or the Greater Seattle Area three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role As an engineer on this team, you will be responsible for building and supporting a petabyte-scale data platform in the cloud and providing powerful foundations for GM ML Data Platform tools, frameworks, and services. Responsibilities include ensuring scalable, transparent, and reliable data ingestion and management; development of fast, robust, and spike-resistant data consumption, data mining, and processing tools for the entire company; and development of orchestration for large-scale post-processing, and computational pipelines. What You’ll Do Lead us in the development, optimization and productionization of the next generation ML data processing platform using Beam and Spark in the cloud. Build self-serve capabilities to help customers to adopt the next generation ML data processing and mining platform Use the latest cloud technologies to own, design, implement, and test scalable distributed data systems in the cloud. Champion engineering excellence by continuously improving systems and processes Own technical projects from start to finish, contribute to the team’s product roadmap, and be responsible for major technical decisions and tradeoffs. Effectively participate in team’s planning, code reviews and design discussions Consider the effects of projects and proactively manage conflicts. Work together with partner teams and orgs to achieve cross-organizational goals and satisfy broad requirements Conduct technical interviews with well-calibrated standards and play an essential role in recruiting activities. Effectively onboard and mentor junior engineers and/or interns