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Website: redwoodmaterials.com
Redwood Materials, Inc. is an American company headquartered in Carson City, Nevada. The company aims to recycle lithium-ion batteries and produce battery materials for electromobility and electrical storage systems. Founded in 2017 by J. B. Straubel, Redwood Materials was reported to have a valuation of about $6 billion as of October 2025.
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Redwood Materials is hiring a Senior Analytics Engineer in San Francisco, California, United States for a full-time role focused on building production data systems that advance battery materials circularity. You will engineer code-first pipelines and analyses that deliver reliable insights to core business teams. Position Summary The central data and analytics team at Redwood Materials develops and sustains the pipelines that enable reporting, insights, and automation company-wide. This Senior Analytics Engineer position is hands-on engineering work: most time is spent writing code for pipeline construction, automated analyses, and production maintenance rather than living inside BI interfaces. You partner directly with finance, supply chain, and operations colleagues to clarify needs, define technical scopes, and ship dependable automated data products that hold up under real-world use. Success means converting business discussions into well-built, production-ready pipelines you fully own. Day-to-Day Responsibilities Construct, launch, and support production-ready automated data pipelines coded in Python and SQL. Execute one-time and recurring analyses grounded in financial models and supply chain calculations. Translate stakeholder conversations and business value drivers into scoped technical pipeline and automation designs. Orchestrate workflows with solutions such as Dagster or Airflow and manage transformations using dbt. Apply version control, testing, code review, and CI/CD practices to every data workflow. Run pipelines on cloud infrastructure while safeguarding the ongoing reliability of deployed assets. Collaborate with finance, supply chain, and operations partners to furnish the metrics, datasets, and automations they depend on. Drive complete ownership of delivery, covering scoping, priority setting, and follow-through to completion. What We're Looking For Three or more years constructing, launching, and maintaining production data pipelines. Bachelor’s degree in a quantitative or technical discipline such as data engineering, computer science, or applied mathematics; graduate degree preferred. Domain knowledge of financial metrics or of supply chain and operations processes. Strong command of Python and SQL. Experience with orchestration platforms such as Dagster or Airflow together with dbt. Working familiarity with cloud infrastructure. Comfort with CI/CD workflows and sound software engineering practices. Demonstrated ability to derive technical pipeline and automation solutions from stakeholder talks and business context. Prior AWS exposure, dual-domain expertise across finance…
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