Data Engineering Lead for Real-Time Analytics

Starbucks Corp.; Nashville (TN); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

401(k)

Tuition assistance

Job summary

Starbucks Technology Nashville is recruiting a data engineer lead to build enterprise data services and analytics solutions. You will own design, development, testing, and support for data pipelines enabling real-time and batch processing tailored to business needs.

You will mentor peers and drive best practices across the team. The role emphasizes architecture, governance, and collaboration with cross-functional teams to deliver scalable data platforms on AWS or Azure, with a focus on

Qualifications

• Bachelor's degree in computer science, MIS, or related field.
• 2+ years in software development.
• 5-7+ years architecting and designing large-scale distributed systems.
• 5+ years SQL platform experience.
• 2+ years exposure to No-SQL platforms is a plus.
• 2+ years CI/CD experience.
• 2+ years exposure to SOA architecture.

Responsibilities

• Lead data engineering team to build and support batch, distributed and real-time data pipelines.
• Translate requirements into data solutions to meet business needs.
• Define data retention and governance policies and procedures.
• Develop and maintain documentation for all systems and projects.
• Mentor teammates and drive best-practice coding standards.

Skills

Data engineering

Big data

SQL

NoSQL

Hadoop

Spark

Cloud platforms

CI/CD

Java/Scala/C# knowledge

Python

Education

Bachelor's degree in CS/IS or related

Tools

Azure

AWS

ETL tooling

Git/CI tooling

Job description

Starbucks Technology Nashville is recruiting a data engineer lead to build enterprise data services and analytics solutions. You will own design, development, testing, and support for data pipelines enabling real-time and batch processing tailored to business needs.

You will mentor peers and drive best practices across the team. The role emphasizes architecture, governance, and collaboration with cross-functional teams to deliver scalable data platforms on AWS or Azure, with a focus on