Senior Analytics Platform Engineer; AI-Native Analytics

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.

The analytics landscape is shifting: from passive dashboards to active, agentic systems. The Core Data team is building a best-in-class platform to support that shift, enabling exploration, reporting, and decision-making across the enterprise.

make everyone a data person. We build the platforms, products, and guardrails that allow thousands of users—engineers, operators, analysts, executives, and AI agents—to access, explore, and act on trusted data with speed and confidence.

As a Senior Analytics Platform Engineer (AI-Native Analytics), you will own and evolve the analytics ecosystem that makes this possible. This is a hands-on engineering role with significant influence over the direction of our platform. You will operate at the intersection of data engineering, platform engineering, and AI—shaping how both humans and agents interact with data.

This role goes beyond traditional platform operations. You will join the team that is defining and executing a multi-year vision for AI-native analytics
, expanding our platform to support context-aware self-serve, conversational, and agent-driven workflows. Your work will lower barriers to entry, reduce friction, and enable a step-change in how data is used across the company.

• Design, build, and operate a modern analytics ecosystem grounded in Databricks and dbt
  , integrating AI-native capabilities directly into the platform strategy.

• Build and maintain infrastructure for agentic AI solutions
  , implementing patterns for context-aware analytics, high-quality metadata, and multi-step reasoning.

• Drive performance, reliability, and scalability improvements across the Analytics AI Platform
  , ensuring the ecosystem stays ahead of best-in-class patterns.

• Develop conversational analytics and intuitive platform tools to democratize data access, making everyone a "data person" through AI-driven discovery.

• Implement robust Access Control List (ACL) frameworks and governance standards to ensure trusted, secure, and compliant data democratization.

• Partner with teams to translate ambiguous business requirements into technical blueprints, moving special projects rapidly into production.

• Provide training, support, and clear guidance to the broader data community to reduce friction and foster a culture of continuous learning.

Minimum Qualifications:

• 6+ years of experience building and scaling enterprise-grade analytical platforms and production data systems.

• Strong proficiency in Python and SQL with the ability to write production-ready, scalable code.

• Hands-on experience with Databricks ecosystem and mastery of dbt for ETL/ELT orchestration and large-scale data warehousing.

• Proven ability to build and maintain infrastructure for agentic AI, enabling autonomous agents to perform complex discovery and conversational workflows.

• Proficiency with Terraform (or similar tools) for managing and deploying analytics infrastructure, alongside standard Git workflows.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

Preferred Qualifications

• Experience working with Databricks ecosystem and Hex.

• Exposure to Fivetran.

• Experience building reliable evaluation frameworks for AI systems and metadata layers.

• Ability to lead the enterprise through the adoption of emerging best practices and AI-driven platform analytics.

• Experience with Context Engineering and designing machine-readable metadata to minimize LLM hallucinations.

• Demonstrated ability to move special projects from ambiguity to production-ready…