Senior Cloud Engineer, Data Platforms
About Rivian
Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
Role Summary
We are looking for a Senior Data Engineer who thrives at the intersection of high-performance data development and platform stewardship. In this role, you aren’t just a passenger on the roadmap—you are a key contributor to how we build. You will spend your time crafting sophisticated data pipelines while taking a high-level interest in the health, setup, and evolution of our Databricks Platform. We value a "Senior Mindset"— someone who naturally looks at a solution and asks, "How can we make this more scalable, more efficient, and more future-proof?" We don't believe in manual drudgery. Our team stays ahead of the curve by integrating the world’s most advanced AI tools into our daily workflows. You will have full access to Gemini, Claude, Cursor, Windsurf, and Devin to accelerate architecture design, automate boilerplate, and focus your energy on solving complex logic and platform challenges.
Responsibilities
● Hybrid Engineering & Platform Ownership: Balance the delivery of high-impact data pipelines with the responsibility of maintaining and optimizing our Databricks environment.
● Architectural Influence: Act as a technical consultant within the team. You will proactively propose infrastructure improvements and evaluate new technologies to keep our stack at the cutting edge.
● Advanced Lakehouse Development: Design and deploy modular ingestion and processing pipelines using Lakeflow and Databricks Asset Bundles (DABs) for reproducible, automated deployments.
● Platform Stewardship: Take a primary role in Databricks setup, ensuring the environment is tuned for performance and integrated seamlessly with our wider ecosystem.
● Enterprise Governance: Configure and manage enterprise data lineage and metadata through Unity Catalog, ensuring our data remains a trusted asset.
● Collaborative Engineering: Work alongside Data Scientists to build robust data services using Python, SQL, and dbt, helping translate complex requirements into elegant technical solutions.
Qualifications
●
Experience
4+ years in Data Engineering, with a deep, hands-on understanding of the Databricks ecosystem, is considered a plus.
● The Architect’s Mindset: You enjoy thinking about the "big picture" and have a track record of proposing and implementing technical improvements.
● Core Mastery: Expert-level proficiency in Python, SQL, and dbt (data build tool).
● Modern Tooling: Strong experience with AWS infrastructure (S3, ECS, Lambdas), GitLab CI/CD, and automated data movement via Fivetran.
● Orchestration: Proficiency in automating complex workflows using Managed Airflow or Databricks Workflows.