kartik Somani

I’m a detail-oriented data professional with hands-on experience in data cleaning, quality monitoring, and anomaly investigation across SQL, Python, and ETL pipelines (Snowflake, dbt, PySpark). I’m comfortable working independently across time zones and I focus on maintaining data accuracy and consistency across large datasets to enable trustworthy decision-making.

Through technical internships, I supported data validation and lifecycle reporting—analyzing transit system performance data to track key metrics and identify bottlenecks, and resolving irregular patterns in component diagnostic data to reduce data anomalies. I also build analytics and warehouse-focused projects like a user activation funnel analysis (cleaning event-level data and investigating drop-offs) and a cohort retention dashboard (dbt models + Streamlit monitoring) to flag irregular engagement trends.