You now understand Python for data engineering:
- Pandas works for small data; use chunking, Dask, or Polars for larger files
- PySpark distributes processing across clusters with lazy evaluation
- Airflow DAGs use TaskFlow decorators for cleaner code
- API extraction needs pagination, retries, and rate limiting
- Test transformations with unit tests and fixtures
In coding interviews, write clean, readable code. Handle edge cases. Discuss time and space complexity. time, space is the goal when possible.