Design and deliver high-quality, scalable data products that provide a unified source of truth across a complex ecosystem of 60+ global sub-brands
Build and optimize robust ETL/ELT pipelines to ingest and transform massive volumes of structured and unstructured data
Lead the design of secure, cost-efficient data architectures
Implement rigorous data governance frameworks, including lineage tracking, metadata management, and quality controls
Act as a strategic 'sparring partner' for Analytics, ML, and AI teams
Manage and tune data platforms for peak performance
Mentor junior members and foster a culture of technical excellence

7+ years of professional experience in data engineering or data management
Advanced degree (Masters or PhD) in Computer Science, STEM, or a related quantitative field
Deep hands-on experience with Databricks (PySpark, Delta Lake, Unity Catalog)
Expert-level SQL skills (optimization, indexing) and mastery of data modeling techniques (Dimensional, Star Schema, Snowflake)
Proficiency in at least one major cloud provider (AWS, GCP, etc) and modern orchestration tools like Airflow or dbt
Proven experience managing data across various RDBMS platforms (PostgreSQL, SQL Server, Oracle, etc.)
Strong command of Docker/Kubernetes and commitment to CI/CD best practices
Experience with data versioning, schema evolution, and distributed metadata management

Senior Data Engineer

Key skills