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# Data Engineer

- **Company:** Starbucks
- **Location:** Nashville, TN, United States
- **Experience:** Expert
- **Salary:** $135,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Cloud Computing, Cloud Database, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Systems, Data Warehousing, Digital Technology, Operational Data Store, Power BI, Tableau (Software), Snowflake, Data Management, Stream Processing, Looker Analytics, Software Version Control, Data Pipelines
- **Published:** October 3, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3002563884-2

## About the Role

* SQLPython or Scala
 * ETL/ELT pipeline development
 * Data warehousing (e.g., Snowflake, Redshift, Big
 * Query)
 * Cloud platforms (AWS, Azure, or GCP)
 * Data modeling and schema design
 * Batch and real-time data processing
 * Data governance and quality assurance
 * BI and analytics tools (e.g., Power BI, Tableau, Looker)
 * Version control and CI/CD for data projects

## Description

Starbucks is hiring a Senior Data Engineer to shape data solutions that power store operations, supply chain, and customer insights. In this role, you will design and maintain scalable data pipelines, warehouses, and APIs to integrate data from retail, digital, and enterprise systems. You'll partner with analytics, finance, and operations teams to deliver reliable, well-governed datasets and dashboards. Working in a hybrid model in Nashville, you'll join a collaborative, values-driven culture that emphasizes inclusivity, sustainability, and growth through training, mentorship, and leadership opportunities., * Design, build, and maintain scalable ETL/ELT data pipelines from retail, supply chain, and digital systems

 * Develop and optimize data models and warehouses to support analytics and reporting
 * Implement data quality, governance, and security best practices for sensitive operational data
 * Collaborate with analytics, finance, and operations partners to translate business needs into data solutions
 * Support BI dashboards and self-service analytics for corporate and store stakeholders
 * Monitor, troubleshoot, and improve performance and reliability of data platforms
 * Contribute to cloud-based data architecture standards and reusable components
 * Mentor junior data engineers and promote best practices in coding, testing, and documentation