Data Engineer
Summary
Build and scale a central data ecosystem for 60+ sub-brands, designing ETL/ELT pipelines, optimizing cloud data platforms, and enforcing governance for AI/ML use cases.
As a Senior Data Engineer at team.blue, you will shape the central data ecosystem and build high-value products that act as the single source of truth for 60+ sub-brands. You will scale and govern data assets to power BI, operations, and AI initiatives, collaborating with analytics, ML, and AI teams. This role offers impact through data-driven decision making across a multi-brand environment, with opportunities to mentor and drive architectural excellence. Join a mission to enable fast, reliable insights at scale.
- Design and deliver scalable data products that unify data across 60+ global sub-brands
- Build and optimize ETL/ELT pipelines for large volumes of structured and unstructured data
- Lead secure, cost-efficient data architecture design and enforce best practices in modeling, orchestration, and observability
- Implement data governance with lineage, metadata management, and quality controls for AI/ML use cases
- Serve as a strategic partner to Analytics, ML, and AI teams translating business needs into technical solutions
- Tune data platforms for peak performance, focusing on indexing, query optimization, and schema evolution
- Mentor junior engineers and promote technical excellence
- 7+ years of professional data engineering or data management experience
- Advanced SQL skills with optimization and indexing expertise
- Hands-on Databricks experience (PySpark, Delta Lake, Unity Catalog)
- Cloud proficiency with AWS or GCP; familiarity with modern data stack tools like Airflow or dbt
- Proficiency with Docker and Kubernetes; experience with CI/CD practices
- Experience with data versioning, schema evolution, and distributed metadata management
- Track record deploying stable, high-performance data solutions with measurable business value
- Excellent cross-functional communication and strategic thinking