About Us

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.

Role Summary

About the Team

Enterprise Data is transforming how leaders at RV Tech access information and make decisions.

We are building a trusted enterprise data and AI platform that brings together critical information across People, Finance, Privacy, and Legal. Our goal is to move beyond fragmented reports and dashboards toward a unified experience where leaders can explore certified data, understand the context behind key metrics, and ask complex business questions using natural language.

The team owns the data foundations, semantic models, AI capabilities, and analytical experiences that make this possible.

About the Role

We are looking for a Staff Data Engineer to provide technical leadership for our enterprise data and AI platform.

You will design and build trusted data products, establish architecture and engineering standards, and solve complex problems spanning ingestion, transformation, semantic modeling, governance, and AI-powered analytics. You will remain hands-on while setting the technical direction for initiatives that cross multiple business domains and systems.

This role requires more than building pipelines. You will work closely with senior leaders and domain experts to understand how the business operates, turn ambiguous questions into durable data products, and ensure that AI-generated insights remain accurate, explainable, secure, and grounded in certified enterprise data.

You will have the opportunity to shape both the platform and the engineering culture behind one of RV Tech’s most visible internal data products.

Responsibilities

• Certified Data Backbone: Design and implement scalable ELT pipelines and semantic models using dbt, SQL, and Python on Databricks. Own the end-to-end data lifecycle—including ingestion, transformation, governance, certification, semantic modeling, data quality, observability, and lineage—to deliver enterprise-grade certified datasets that power executive decision-making.

• Executive Analytics Applications: Architect and contribute to a unified, React-based executive analytics portal, transitioning the C-suite experience from fragmented dashboards to a centralized, application-driven environment with embedded analytics, AI-assisted insights, and trusted enterprise access.

• Agentic AI & Context Engineering: Design and deploy conversational AI agents over enterprise data products by building metadata and semantic frameworks, implementing RAG pipelines and reasoning engines, and establishing guardrails that ensure safe, compliant, and context-aware AI interactions with certified data.

• Cross-Functional Executive Partnership: Serve as the primary technical partner to senior leaders across Finance, People, Privacy, and Legal, translating strategic priorities into scalable data products, aligning diverse stakeholders, and influencing executive analytics strategy.

• Strategic Engineering Leadership: Define and uphold end-to-end engineering standards across the Enterprise Insights domain, including scalable architecture, Infrastructure as Code (Terraform), CI/CD, version control best practices, operational SLAs, and a culture rooted in AI-native design, disciplined experimentation, and operational excellence.

Qualifications

• Full-Stack Technical Mastery: 8+ years of experience in Data or Software Engineering with expert-level SQL and Python skills, including advanced query design, performance tuning, data manipulation, and scalable automation. Strong system design and architecture expertise, with a proven ability to build efficient, maintainable, and scalable data systems.

• Modern Analytics & Data Platform Engineering: Deep proficiency with dbt and modern cloud data platforms (Databricks preferred), including semantic layer modeling, business logic abstraction, and implementation of robust data quality, governance, and lineage frameworks.

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