Senior Analytics Engineer Redwood Materials
Battery recycling for a sustainable circular supply chain.
Permanent
San Francisco
Remote: Not specified
Salary: Not specified
> 3 years
Skills we're looking for
Financial modeling
Cloud & infrastructure
Project management
Continuous deployment
DBT
+5
You'll be part of
849 employees
Our take
Redwood Materials, the brainchild of former Tesla co-founder and CTO JB Straubel, is making waves in the sustainable energy sector with its strategic approach to battery recycling and domestic supply chains for lithium-ion batteries. The company is dedicated to creating a fully closed-loop supply chain by manufacturing critical battery components using as many recycled batteries as possible, effectively localising a 50,000-mile global battery supply chain on a single site. This strategy aims to address the critical issue of material sourcing, particularly the reliance on China for battery materials. Redwood Materials closed a Series E funding round in 2025 at a post-money valuation exceeding $6B. This financial backing positions the company to continue expanding its capacity, further strengthening the US's domestic battery supply chain. Its ambitious goal of enabling customers to purchase battery materials made in the US is aligned directly with the broader political objective of onshoring critical industries, as emphasised in the USA's 2022 Inflation Reduction Act.
You'll be working on
- Our central data and analytics team builds and operates the data pipelines that power reporting, analytics, and automation across Redwood
- This is a hands-on engineering role: the majority of our work is code-based data pipelining and automated data analyses
- You will spend most of your time on code-based analysis and building and maintaining production pipelines rather than working in a BI tool
- You will work directly with stakeholders in finance, supply chain, and operations to understand what they need, scope technical solutions, and deliver reliable, automated data products
- We are looking for someone who can translate a business conversation into a well-engineered pipeline and stand behind it in production
- Build, deploy, and maintain production-grade automated data pipelines using Python and SQL
- Perform one-off and automated data-driven analyses using financial and supply chain models and calculations
- Scope technical pipeline and automation solutions based on conversations with users and an understanding of the underlying business value drivers
- Develop and orchestrate pipelines using tools such as Dagster or Airflow, and manage transformations with dbt
- Apply CI/CD and sound software engineering practices (version control, testing, code review) to data workflows
- Deploy and run pipelines on cloud infrastructure, and help maintain the reliability of what we ship
- Partner with finance, supply chain, and operations stakeholders to deliver the metrics, datasets, and automations they rely on
- Own delivery of your work end to end, including scoping, prioritization, and follow-through
We're looking for
- Familiarity with CI/CD and good coding practices
- Ability to scope technical data pipeline solutions and automations from stakeholder conversations and business context
- Strong Python and SQL
- Domain expertise in financial metrics or in supply chain and operations
- Minimum bachelor’s degree in quantitative or technical field such as Data Engineering, Computer Science, Applied Math, etc. Graduate degree preferred
- Working knowledge of cloud infrastructure
- Experience with orchestration tools such as Dagster or Airflow, and with dbt
- 3+ years building, deploying, and maintaining production data pipelines
- Experience with AWS
- Domain expertise across both financial metrics and supply chain/operations
- Project management skills
- Experience with Starburst and OpenMetadata