Analytics Engineer II, Product Development at Rivian in US-CA-Irvine

Summary: Rivian is an innovative company focused on developing electric vehicles, and they are seeking an Analytics Engineer to support their Product Development organization. The role involves architecting data foundations, building reliable data infrastructure, and providing data-driven insights to optimize product and process outcomes. Responsibilities: - Architect the Source of Truth: Develop and maintain production-grade data models in Databricks and dbt that unify high-velocity vehicle telemetry and charging session data. Build reliable, fast, and dynamic data tools, pipelines, and automated workflows that scale with our growing fleet and charging network - High-Fidelity Reporting: Design and deploy clear, effective dashboards and apps in tools like Plotly Dash that adhere to strict performance SLAs and design quality standards for a wide range of stakeholders including executive leadership as well as external partners - Telemetry Insights: Extract and contextualize complex data from telemetry and business systems to identify performance bottlenecks and drive technical improvements in a range of outcomes across product development and business strategy. Assess the effectiveness and accuracy of new data sources and data gathering techniques - Engineering Rigor: Implement software development best practices – including version control (Git), unit testing, CI/CD, and data quality monitoring – into the data lifecycle to ensure our reporting is as reliable as the vehicles we build Required Qualifications: - Bachelor's, master's, or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Materials Science, Physics, Mathematics, or another quantitative field - 0-4 years of experience building production data pipelines and developing AI/ML solutions - High level of programming proficiency in Python and SQL. You should be comfortable writing clean, modular code and querying complex relational databases - Analytics Engineering Mindset: Experience with and a strong desire to master dbt (data build tool) and Databricks/Spark environments - Software Fundamentals: Demonstrated experience with version control (Git) and an understanding of how to move a model from a notebook to a stable, reproducible environment - Domain Context: Prior experience or interest in physical engineering systems (Hardware, IoT, or Telemetry) - Strong problem-solving skills with an emphasis on product development - Excellent written and verbal communication skills for coordinating across teams and leading cross-functional efforts. Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions - A drive to learn and master new technologies and techniques Preferred Qualifications: - UI/Visualization: Experience building user-facing applications using tools like Plotly Dash, Streamlit, and Hex - DevOps for Data: Familiarity with Linux environments and CI/CD workflows for data pipelines - Advanced Stats: Knowledge of statistical concepts (regression, distributions) to help validate the accuracy of the models you support - Exposure to or hands-on experience with LLM application concepts such as retrieval, grounding, prompt/agent design, function/tool use, evaluation, safety/guardrails, and cost/latency optimization - Passion: An obsession with electric vehicles, renewable energy, and the future of sustainable transportation Required Skills: Python, SQL, Databricks, dbt, Data modeling, Data pipelines, Data analysis, Data mining, Version control - Git, CI/CD, Unit testing, Data quality monitoring, Telemetry data, Physical engineering systems Benefits: Paid vacation, Paid sick leave, Life insurance, Medical insurance, Dental insurance, Vision insurance, Short-term disability insurance, Long-term disability insurance, 401(k) Plan, Employee Stock Purchase Program