Tell me about a time when you designed and deployed an automated data validation workflow that reduced data entry errors by a measurable percentage across multiple clinical sites.

STAR + step‑by‑step strategy (120‑150 words, no story). 1. Situation: Identify recurring data errors. 2. Task: Reduce error rate. 3. Action: 1) Map error patterns, 2) Define validation rules, 3) Build automated workflow (SQL + ETL), 4) Pilot on 2 sites, 5) Rollout, 6) Monitor KPIs. 4. Result: Quantified improvement and compliance impact.

I noticed that duplicate and out‑of‑range lab values were a recurring source of queries, inflating our data cleaning workload. I mapped the error patterns, identified that 18% of entries were duplicates and 12% exceeded reference ranges. I designed a set of SQL‑based validation rules and integrated them into our nightly ETL pipeline. After a pilot on two sites, I refined the rules and rolled out the workflow across all 12 sites, providing training and a quick‑reference guide. Within three months, the error rate fell 35%, reducing query volume by 40% and ensuring compliance with FDA 21 CFR Part 11. The project was highlighted in the quarterly data quality dashboard and received commendation from the CRO.