Director of Data

Rivian and Volkswagen Group Technologies•Palo Alto, CA

8d•Hybrid

About The Position

Rivian and Volkswagen Group Technologies is a joint venture between two industry leaders with a clear vision for automotive’s next chapter. From operating systems to zonal controllers to cloud and connectivity solutions, we’re addressing the challenges of electric vehicles through technology that will set the standards for software-defined vehicles around the world. The road to the future is uncharted. By combining our expertise across connectivity, AI, security and more, we’ll map a new way forward. Working together, we’ll create a future that’s more connected, more intelligent, more sustainable for everyone. We are looking for a Director of Data to own our data strategy and platform as we scale toward software-defined vehicles. This is a hands-on leadership role where you'll set technical direction and stay close to the architecture and code, while building and managing a high-performing team responsible for high-volume, high-velocity vehicle and enterprise data. You'll bring both the technical depth to make sound platform decisions and the people leadership to grow and run a team operating at scale. We're hiring for this role in Palo Alto, Irvine, or Vancouver. We are happy to work with whichever location suits you best.

Requirements

8–10 years of overall industry experience in data engineering or analytics, including 3+ years managing high-volume data engineering or analytics teams.
Demonstrated hands-on technical depth in building and operating large-scale data systems, proficiency in SQL and Python required, along with hands-on experience with Databricks required (additional experience with Spark or equivalent distributed data platforms a plus).
Track record of designing and scaling data architecture (ingestion, ETL/ELT, streaming, and storage) for high-volume, high-velocity data.
Experience hiring, developing, and retaining data engineering talent, with a demonstrated ability to balance IC-level technical involvement with people leadership.
Strong cross-functional partnership skills and being comfortable working with engineering, product, quality, and manufacturing stakeholders to translate business needs into data infrastructure.
Experience establishing data governance, quality, and security practices at an organizational level.
Bachelor's degree in Computer Science, Data Engineering, Electrical Engineering, or a related technical discipline; advanced degree a plus.

Nice To Haves

Experience in automotive, mobility, IoT, or another industry with high-volume sensor/telemetry data.
Experience integrating or prompting AI/LLM tools into engineering workflows.
Familiarity with dashboard/BI tooling (HEX, Tableau, Power BI, or similar) for stakeholder reporting.

Responsibilities

Define and drive the data strategy and roadmap across vehicle telemetry, manufacturing, and enterprise data domains, aligning with engineering, product, and business stakeholders.
Own architecture decisions for large-scale data platforms (ingestion, storage, processing, and serving layers) handling high-volume streaming and batch data.
Stay hands-on: review designs and code, dive into pipeline or performance issues, and set technical standards by example, not just by policy.
Recruit, manage, mentor, and grow a team of data engineers and analytics professionals; own hiring plans, performance management, and career development.
Partner with quality, manufacturing, product, and software engineering teams to ensure data infrastructure supports reliability, safety, and product analytics needs.
Establish data governance, quality, and security standards across pipelines and platforms, ensuring compliance with relevant regulatory and privacy requirements.
Build and maintain stakeholder-facing reporting on platform health, data quality, and delivery against roadmap commitments.
Evaluate and integrate modern tooling (e.g., Databricks, Spark, Kafka, cloud data warehouses, AI/LLM-assisted engineering tools) to keep the platform and team ahead of scale demands.
Manage budget, vendor, and tooling decisions for the data organization.