

Detail-oriented ETL & Data QA Engineer with 4+ years of experience validating data pipelines, ETL/ELT processes, dashboards, and large-scale data transformations. Skilled in SQL, Pyapark, Databricks, Delta Lake, Data Lake validation, and Snowflake. Strong experience in ETL work flow validations, Data integrity,Data reconciliation,Data completeness,Migration testing, and cloud-based data storage and pipelines validation using ADF, ADLS, and Databricks notebooks.
Medical claims project (Jun-2022 to Dec-2023) Performed end-to-end ETL testing across source, staging, and target layers to ensure data accuracy, integrity, completeness, Validated data transformations , aggregations using complex SQL queries., Conducted data quality checks, including null, duplicate, and referential integrity validation., Executed incremental load validation and collaborated with data engineers to resolve ETL failures., Documented test cases, execution results, and defects using JIRA, Supported data reconciliation and BI report validation to ensure business reporting accuracy, Participated in requirement walkthroughs and defect triage to improve data quality.
On-Prem to Cloud Migration Projects (Jan-2024 to Feb-2026) Validated ETL migration from on-prem SQL Server/Oracle to Databricks Delta Lake., Performed source-to-target data validation using SQL & PySpark (count comparisons minus/except)., Conducted schema, data type, completeness, and integrity checks across environments., Validated full and incremental loads, ensuring historical and delta data accuracy., Used Databricks Notebooks, Azure Data Factory (ADF), and ADLS to validate and monitor pipelines., Verified CDC logic and timestamp handling to ensure correct incremental data processing., Worked closely with engineering teams to identify data mismatches and optimize validation logic.