Senior Data Pipeline Engineer — Production Analytics

Redwood Materials; Sparks (NV); On-site; USD 120,000 - 160,000; Full time

Job summary

Redwood Materials is seeking a data engineer to build production data pipelines powering finance, supply chain and operations. This hands-on role focuses on code-based data analysis and automated pipelines, not BI tooling.

You will own end-to-end delivery from scoping to deployment, collaborating with stakeholders, and deploying on cloud infrastructure using Python, SQL, Dagster or Airflow, and dbt.

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 supply chain/operations.
• Strong Python and SQL.
• Experience with Dagster or Airflow and dbt.
• Working knowledge of cloud infrastructure.
• Familiarity with CI/CD and coding best practices.
• Ability to scope technical data pipeline solutions from stakeholder conversations.

Responsibilities

• Build, deploy, and maintain production-grade automated data pipelines using Python and SQL.
• Perform data-driven analyses using financial and supply chain models.
• Scope technical pipeline and automation solutions based on stakeholder conversations.
• Develop and orchestrate pipelines using Dagster or Airflow, and manage transformations with dbt.
• Apply CI/CD and sound software engineering practices to data workflows.
• Deploy and run pipelines on cloud infrastructure and maintain reliability.
• Partner with finance, supply chain, and operations stakeholders to deliver metrics and datasets.
• Own end-to-end delivery including scoping, prioritization, and follow-through.

Skills

Python

SQL

CI/CD

Code quality

Stakeholder collaboration

Education

Bachelor's degree in quantitative or technical field

Tools

Dagster

Airflow

dbt

AWS

Job description

Redwood Materials is seeking a data engineer to build production data pipelines powering finance, supply chain and operations. This hands-on role focuses on code-based data analysis and automated pipelines, not BI tooling.

You will own end-to-end delivery from scoping to deployment, collaborating with stakeholders, and deploying on cloud infrastructure using Python, SQL, Dagster or Airflow, and dbt.