Every Sunday I take 15 minutes to look back at the week — not to celebrate wins or beat myself up over mistakes, but to actually learn from both.
This week was a mix of small victories and honest face-palm moments. Here’s what happened, what I’d do differently, and what I’m carrying into next week.
The Win That Actually Mattered
Early in the week I finally automated a messy ingestion job that I’d been running manually for months. A couple hours of Python scripting later, that job now runs on a schedule, logs its own errors, and sends an alert if something looks wrong.
That’s roughly 2 hours a day back. Ten hours a week. Five hundred hours a year if you run the math.
The lesson: the automation you keep putting off is almost always worth it.
The Mistake I Won’t Make Again (Hopefully)
Mid-week I hit a cryptic error in a dbt model and spent nearly four hours staring at YAML and SQL. Finally I described the problem in a Slack message to a teammate. Their reply came in 8 minutes with the exact fix.
Four hours of solo suffering. Eight minutes with a teammate. Ask for help faster. It’s not a weakness. It’s engineering.
What Finally Clicked: Airflow Dynamic Task Mapping
This week I used Airflow’s dynamic task mapping on a real pipeline. Instead of hardcoding 12 parallel tasks for 12 data sources, I mapped a single task over a list — and Airflow handled the fan-out automatically. The DAG went from 80 lines to 30.
# Before: hardcoded tasks
process_source_a = PythonOperator(task_id='process_a', ...)
process_source_b = PythonOperator(task_id='process_b', ...)
# After: dynamic mapping
process_sources = PythonOperator.partial(
task_id='process_source',
python_callable=process_fn
).expand(op_args=get_source_list())The Theme of the Week: Collaboration Over Heroics
Almost everything good this week came from using other people’s knowledge, patterns, or experience. Solo heroics are satisfying in the moment, but the team is a resource — not a last resort.
What I’m Carrying Into Next Week
- Automate the annoying thing — if you’re doing it manually more than twice, schedule it.
- Ask the question — pride is expensive. Curiosity is free.
- Read the docs slowly — most features are well-documented; we just skim.
- Collaboration first — the team knows things you don’t, and vice versa.
If you’re a data engineer reading this on a Sunday: what’s your biggest lesson from the week? Drop it in the comments.
— Pushpjeet Cholkar, Data Engineer