Barsha Pandey

I’m a Data Engineer with 3+ years of experience specializing in data transformations and performance tuning for high-volume healthcare data. I build and maintain scalable ETL pipelines using PySpark and AWS, ensuring data quality, security, and HIPAA compliance. In my current role, I managed ingestion and large-scale processing of healthcare claims datasets using Snowflake and AWS infrastructure.

I built automated ETL pipelines using AWS Lambda and AWS Step Functions to orchestrate ingestion and processing from AWS S3, eliminating manual workflows. I optimized SQL queries and stored procedures, reducing daily processing time by 20–40%, and designed reusable frameworks for schema standardization, column normalization, and dataset validation. I also create clean, analytics-ready master datasets for reporting and BI, and I monitor/troubleshoot production pipelines to improve reliability. Earlier, I completed a Financial Data Analyst apprenticeship using Pandas/Numpy and built predictive models (linear/logistic regression) plus time series analysis, and I interned as a Python Developer contributing to a Nepali Text-to-Speech (TTS) GUI using Python (Tkinter). I’m excited to bring this mix of engineering rigor and analytics mindset to teams that care about secure, dependable data.