How would you use Python and SQL together in a data engineering apprenticeship?

08 July 2026

Question

How would you describe your use of Python and SQL for transformation tasks in a cloud data platform?

I would describe Python and SQL as complementary tools.

SQL: I would use SQL when the task is relational and set-based, for example filtering records, joining tables, aggregating measures and building curated views. - Python: I would use Python when I need more control over program flow, reusable functions, file handling, validation logic, parameterisation or integration with APIs and notebooks. - In Databricks: A practical pattern is using SQL for transformations on structured datasets and Python for orchestration, reusable checks and notebook logic. - Maintainability: I would keep code readable, modular and well-named, and I would avoid overcomplicating solutions when a clear SQL transformation is enough. - Testing Mindset: I would validate row counts, check schema changes and compare sample outputs so I know the transformation behaved as intended. A strong answer for this role is that I am comfortable using both languages appropriately: SQL for expressing data logic clearly, and Python for building robust, reusable engineering workflows around that logic.