Sudama Pandit

Domain: Healthcare (USA-based client) * Designed scalable ETL/ELT pipelines using Python, PySpark, SQL, and GCP. * Built and optimized BigQuery workflows and data models for analytics. * Architected event-driven pipelines using Google Pub/Sub for real-time ingestion. * Implemented CI/CD with Jenkins and GitHub, reducing manual deployment errors. * Developed reusable Python/PySpark frameworks for standardized pipeline development. * Applied Claude Code and GenAI to accelerate development and delivery.

Domain: Travel & Hospitality (USA-based client) * Designed and optimized Snowflake ETL workflows on AWS/GCP. * Developed advanced SQL in Python and optimized queries for performance. * Built reusable Python libraries for ETL automation and orchestration. * Orchestrated pipelines using Apache Airflow. * Integrated GenAI/LLM for automated data quality validation. * Optimized SQL for Data Ops, reducing cloud costs.

Domain: Healthcare (USA-based client) * Designed ETL pipelines using Python, PySpark, SQL, Snowflake, AWS S3, and GCP. * Developed SQL queries and managed version control using Git. * Managed scheduling and monitoring with Azkaban, DBeaver, and Visual Studio. * Reduced cloud costs by 8–10% through SQL optimization. * Maintained 98% SLA compliance across SLAs/OLAs. * Built Python ETL alerting and consolidated jobs for easier debugging.

Domain: Retail & Technology (USA-based client) * Built analytical dashboards using PostgreSQL, Snowflake, and Power BI. * Developed advanced SQL queries and led weekly client meetings. * Built ETL pipelines using Python, SQL, Snowflake, SSIS, AWS S3, and GCP. * Used Git, Apache Airflow, DBeaver, and Visual Studio for development and orchestration. * Improved query performance through targeted performance tuning. * Transformed raw data into accurate PostgreSQL/Snowflake tables.

Domain: Banking & Financial Services (UK-based client) * Troubleshot and resolved SSIS ETL job issues independently and with senior support. * Diagnosed job slowness and performance bottlenecks with cross-functional teams. * Developed and optimized SQL queries to reduce runtime and resource usage. * Supported ETL management, performance tracking, and reporting using SSMS, SSIS, SQL, Python, Airflow, and Power BI.