Anwesha Chowdhury

AWS Certified Data Engineer with 2+ years of experience designing scalable ETL/ELT pipelines using Python, PySpark, and AWS. Experienced in building data warehouses, optimizing SQL queries, and developing healthcare analytics solutions.

Data Engineer (Client-Canon Medical Science & Corporation) - Capgemini Technology Solution India Ltd - Pune, India

(2024-03)

• Designed and implemented a layered data lake architecture (Raw, Processed, Curated) on Amazon S3 storing ~ 2TB healthcare datasets for scalable analytics.
• Developed scalable batch ETL pipelines using AWS Glue (PySpark) to process patient admissions and imaging datasets, improving data availability for reporting and analytics.
• Built and optimized a dimensional data warehouse model (star schema) in Amazon Redshift with fact and dimension tables to enable BI reporting.
• Implemented incremental batch loading logic to process daily hospital records, reducing data latency and improving reporting efficiency by 30%.
• Applied partitioning, query optimization, and performance tuning techniques in Redshift and Athena to enhance query performance.
• Enabled ad-hoc analytics using Amazon Athena for operational insights across clinical and administrative datasets.
• Designed monitoring and logging framework using Amazon CloudWatch to ensure pipeline reliability and SLA compliance.

Bachelor of Technology (B.Tech) - Biomedical Engineering - Maulana Abul Kalam Azad University of Technology (WBUT) (2019 - 2023)

Higher Secondary (12th) - WBCHSE (2018 - 2019)