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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer, Ops Decision Systems - **Company:** Rivian - **Location:** Palo Alto, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Automation of Tests, Code Review, Continuous Integration, Python (Programming Language), Machine Learning, Operational Databases, SQL Databases, Deep Learning, Gitlab, Git, Information Technology, Modeling and Simulation, Performance Monitor, Tools for Reporting, Marketplace, Looker Analytics, Data Pipelines, Databricks - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eead309102a709c2 ## About the Role * Proficiency with Python, SQL, and Databricks (or equivalent warehouse/lakehouse platform); experience with dbt or equivalent transformation frameworks. * Experience with Git-based engineering workflows, code review, and CI/CD pipelines (GitLab or equivalent). * Demonstrated experience owning production data infrastructure end-to-end, including data modeling, pipeline orchestration, testing, and deployment. * Demonstrated ability to design and validate applied simulation and optimization models, including capacity modeling, operational optimization, or multi-variable simulation over multi-year horizons. * Experience reasoning about supply/demand constraints, depreciation mechanics, holding costs, and operating expense, and translating operational decisions into dollar-denominated outcomes. * Demonstrated ability to translate ambiguous operational questions into production data products and durable models., * Bachelor's degree or higher in a quantitative or technical field (Computer Science, Data Science, Statistics, Mathematics, Industrial Engineering, or similar). * Experience applying machine learning or deep learning methods to capacity, logistics, or operational forecasting problems. * Experience integrating external APIs and third-party data sources into production data systems. * Experience with AI-assisted development workflows and agentic coding tools. * Experience in automotive, marketplace, e-commerce, supply chain, or adjacent operations domains. * Familiarity with BI and analytics tools such as Hex, Looker, or equivalent. ## Description This is a technical individual contributor role that designs, builds, and operates the operations-side modeling and simulation systems for Rivian's remarketing business: inventory allocation, reconditioning capacity, disposition timing, logistics, and operating expense. The role develops multi-variable simulation and optimization models in Python and Databricks within Git-versioned repositories with code review, automated testing, and CI/CD, and translates operational levers into dollar-denominated outcomes. The Sr. Data Engineer, Ops Decision Systems role combines applied data science, analytics engineering, and operations ownership: the role both engineers the simulation systems and is accountable for the quality of the operational decisions they inform. Success is measured by the technical robustness of the systems built and the integrity of the plans they produce. * Design, build, and operate production simulation and optimization systems. Develop Python-based simulation models in Databricks as a member of a highly technical team designing interconnected models. Work in Git-versioned repositories with merge-request review, automated testing, and CI/CD pipelines (GitLab), and apply AI-assisted and agentic development workflows as a standard part of the engineering stack. * Statistical and optimization model development. Design, validate, and maintain the models that drive operational decisions: reconditioning capacity and throughput models, operating-expense models, inventory allocation optimization, and disposition-timing models. Apply statistical, machine learning, and optimization methods, with backtesting and production performance monitoring. * Operations data products and pipelines. Build and maintain the data models and pipelines that describe operational performance, covering inventory state, auction outcomes, reconditioning throughput and cost, logistics, and allocation, with data contracts, tests, and documentation that allow downstream decision systems and planning tools to consume them reliably. * AI-augmented engineering. Apply AI-assisted and agentic development workflows as a first-class part of the engineering stack. Evaluate and integrate AI tooling into production engineering workflows and set the patterns the team follows. * Network and capacity scenario engineering. Build and run multi-variable scenario models that optimize the physical infrastructure footprint, vehicle movement strategies, reconditioning capacity plans, and operational workflows across Remarketing operations. Vary levers systematically and narrow many candidate plans to defensible recommendations. * Financial efficiency optimization. Model and trend resource-efficiency outcomes across all areas of operating expense, including reconditioning, storage capacity and utilization, and vehicle movements, and translate operational decisions into projected P&L outcomes over multi-year horizons. * Supply deployment with business partners. Model the prioritization of units for reconditioning, the routing of vehicles toward demand, and the strategic deployment of inventory to maximize profit and stability. Work with customer-focused colleagues to integrate demand signals, and operationalize recommendations with Remarketing operations leadership, internal service and delivery partners, and external third-party partners. ## Related Videos - [Industrializing your Data Science capabilities](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies](https://www.wearedevelopers.com/videos/251-remote-driving-on-plant-grounds-with-state-of-the-art-cloud-technologies) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)