We are looking for a Senior Data Developer to maintain our existing OLAP-based data warehouse while leading the build-out of a modern data platform on Databricks. The role requires strong experience with traditional OLAP and dimensional modelling, combined with hands-on expertise in modern data engineering, cloud, and Lakehouse concepts.
Key Responsibilities
- Maintain and support the current OLAP / data warehouse environment during the transition to the new platform
- Design, build, and optimize scalable data pipelines and data models on Databricks (Spark, Delta Lake, etc.)
- Migrate legacy ETL, reporting, and analytical workloads to a modern, cloud-native data stack
- Ensure data quality, reliability, and performance across both legacy and new environments
- Collaborate with analytics, product, and engineering teams to understand data requirements and deliver high-quality datasets
Required Skills & Experience
- Strong SQL and data modeling skills, including dimensional modeling and OLAP concepts
- Hands-on experience with Databricks and Spark for large-scale data processing
- Solid understanding of ETL/ELT patterns, data warehousing, and data quality practices
- Experience working in environments where legacy platforms coexist with modern data architectures
- 5–8 years of experience in data engineering / data development or similar roles
Nice to Have
- Experience with cloud data services (AWS Glue, Azure Data Factory, or similar)
- Familiarity with data governance and cataloging tools
- Exposure to real-time streaming or event-driven data pipelines
Benefits
- Small, sharp team with ownership, direct impact, and minimal bureaucracy
- Competitive salary with annual performance bonuses
- Learning budget for conferences and certifications
- Health insurance for you and your family