Senior Analytics Engineer

NextGenEnergyJobs; San Francisco (CA); On-site; USD 130,000 - 170,000; Full time

Job summary

Redwood is building a local-global battery supply chain, delivering production-grade data pipelines for reporting and automation. The role focuses on code-based data analyses, not BI tooling, and requires translating business needs into scalable data solutions.

You will work closely with finance, supply chain, and operations to deliver reliable datasets and automations while deploying pipelines on cloud infrastructure and maintaining code quality through CI/CD practices.

Qualifications

• 3+ years building, deploying, and maintaining production data pipelines.
• Bachelor’s degree in quantitative or technical field; graduate degree preferred.
• Domain expertise in financial metrics or in supply chain and operations.
• Strong Python and SQL skills.
• Experience with orchestration tools (Dagster/Airflow) and dbt.
• Working knowledge of cloud infrastructure.
• Familiarity with CI/CD and good coding practices.
• Ability to translate stakeholder conversations into scalable data pipelines.
• Experience with Starburst and OpenMetadata.

Responsibilities

• Build, deploy, and maintain production-grade automated data pipelines using Python and SQL.
• Collaborate with stakeholders in finance, supply chain, and operations to scope and deliver automated data products.
• Develop and orchestrate pipelines using Dagster or Airflow, and manage transformations with dbt.
• Apply CI/CD and software engineering practices to data workflows.
• Deploy pipelines on cloud infrastructure and ensure reliability of deliverables.
• Own delivery end-to-end from scoping to follow-through.

Skills

Python

SQL

CI/CD

Cloud

Stakeholder communication

Education

Bachelor's degree in quantitative/technical field

Tools

Dagster

Airflow

dbt

Starburst

OpenMetadata

AWS

Job description

Redwood is localizing a global battery supply chain that seamlessly integrates recovery, reuse, and recycling - keeping critical minerals in circulation and driving the energy transition.

Key Responsibilities

• 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.

Requirements

• 3+ years building, deploying, and maintaining production data pipelines.
• Minimum bachelor’s degree in quantitative or technical field such as Data Engineering, Computer Science, Applied Math, etc. Graduate degree preferred.
• Domain expertise in financial metrics or in supply chain and operations.
• Strong Python and SQL.
• Experience with orchestration tools such as Dagster or Airflow, and with dbt.
• Working knowledge of cloud infrastructure.
• Familiarity with CI/CD and good coding practices.
• Ability to scope technical data pipeline solutions and automations from stakeholder conversations and business context.
• Experience with AWS.
• Domain expertise across both financial metrics and supply chain/operations.
• Experience with Starburst and OpenMetadata.