To improve reliability and transparency in Nielsen’s TV audience measurement pipelines, I built a real-time monitoring and diagnostics tool that ingests over 10 GB of data per day across 10+ production environments.
The tool replaced a multi-day manual diagnostic process with a fully automated workflow running in under 10 minutes, integrating Spark, Airflow, and Python to execute more than 50 analyses daily.
- Designed an end-to-end diagnostic system using PySpark and Airflow
- Created custom logic for time-based validation and second-level metric breakdowns
- Enabled proactive debugging and monitoring by engineering and QA teams
- Supported performance validation on a 200+ GB pilot with over 10,000 households
Tools & Stack
PySpark · Apache Airflow · Python · Databricks · ETL · Pipeline Diagnostics · Time-Series Analysis · AWS S3 · CLI
Demo and Access
Internal enterprise tool. Diagrams and walkthroughs available upon request.