Senior Data Warehousing Engineer

Badgewell is seeking an experienced Senior Data Warehousing Engineer to join the team to work on an interesting off-shore project with a European customer.


  1. Develop data warehouse process models, including sourcing, loading, transformation, and extraction.
  2. Verify the structure, accuracy, or quality of warehouse data.
  3. Map data between source systems, data warehouses, and data marts.
  4. Develop and implement data extraction procedures from other systems, such as administration, billing, or claims.
  5. Design and implement warehouse database structures.
  6. Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.
  7. Provide or coordinate troubleshooting support for data warehouses.
  8. Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.
  9. Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements.
  10. Perform system analysis, data analysis or programming, using a variety of computer languages and procedures.
  11. Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.
  12. Create or implement metadata processes and frameworks.
  13. Review designs, codes, test plans, or documentation to ensure quality.


  • Computer science degree or equivalent experience
  • Experience: 5-7 yrs
  • Technical Skills: SQL, Redshift, Python
  • Experience with Microsoft, Oracle and Teradata technology stack is required.
  • Experience pulling data from 3rd party systems and services (i.e. Netsuite, Facebook, Google Ads, etc.)
  • Experience pulling Google Analytics data via BigQuery
  • Intrinsically motivated
  • Driven to exceed expectations and help others succeed
  • Detail oriented
  • Focused on progressive improvements, start with the scrappy quick win vs. the impossible to obtain perfect solution