Big Data ETL QA Engineer (Azure/Databricks)

SATEESH KUMAR M

ETL Tester Big Data QA Engineer Azure Data Factory Databricks SQL BI Validation *****************@*****.*** +91-886******* Bengalore India linkedinID:www.linkedin.com/in/sateesh-m-b5240b409 PROFESSIONAL SUMMARY

Results-oriented ETL Tester and Big Data QA Engineer with 4.1 years of experience validating enterprise-scale data pipelines on Azure Cloud, Databricks, and ADF at KPMG India. Proven track record of delivering end-to-end ETL/ELT testing across Healthcare and Retail domains — covering extraction, transformation, SCD validations, CDC, delta/incremental loads, and BI dashboard verification. Automated 40%+ of manual reconciliation effort using Python and PySpark, and consistently ensured zero critical data defects in production deployments. Strong command of complex SQL, source-to-target reconciliation, and Agile/DevOps delivery environments. CORE TECHNICAL COMPETENCIES

ETL & Data Validation ETL Testing, ELT Testing, Source-to-Target Reconciliation, SCD Type 1 & 2, CDC, Delta Load, Full Load, Incremental Load, Data Lineage Validation Cloud Technologies Microsoft Azure (ADF, ADLS Gen2, Azure SQL, Azure DevOps), AWS S3, GCP BigQuery

Big Data & Engineering Databricks, PySpark, Apache Spark, SSIS, Informatica PowerCenter, Snowflake

Databases Azure SQL, Oracle 11g, SQL Server, Amazon Redshift, Snowflake Programming & Scripts SQL (Advanced), Python, PySpark, Shell Scripting, UNIX Commands Testing & QA Test Case Design, Test Scenario Analysis, Regression Testing, UAT, Automation Testing, Data Quality Testing, BRD/FRS Analysis, Defect RCA Reporting & BI Power BI (KPI, Drill-down, Dashboard Validation), Tableau, Cognos Tools & Platforms JIRA, Azure DevOps (ADO), TFS, SQUIDS, Git, Agile / Scrum PROFESSIONAL EXPERIENCE

KPMG India — Big Data QA Engineer / ETL Tester Project: Enterprise Health claims Data lake Modernization December 2023 – Present

ETL Tester Big Data QA & Automation Tester Azure Cloud, ADF, Databricks, ADLS Gen2, PySpark, Power BI, SQL Server

Project: Enterprise Healthcare Claims Data Lake Modernization

• Designed and executed end-to-end ETL/ELT test strategy for migration of legacy healthcare claims platform into Azure Data Lake (ADLS Gen2), covering 6+ source systems and 10+ data domains including Claims, Members, Providers, Premium, Billing, and Payments.

• Automated source-to-target reconciliation using Python and PySpark notebooks in Databricks, reducing manual testing effort by 40% and cutting reconciliation cycle time from 2 days to under 4 hours.

• Validated SCD Type 1 & Type 2 dimensions across the Data Warehouse layer, ensuring historical accuracy of member and provider master data across 3+ years of claims history.

• Executed CDC, Full Load, Delta Load, and Incremental Load validation scenarios on 100M+ healthcare records, achieving 99.9% source-to-target data accuracy across all pipeline layers.

• Built PySpark-based automated data quality framework to enforce null checks, duplicate detection, referential integrity, and business-rule validations — covering 100% of critical pipeline models pre-production.

• Validated ADF pipelines including triggers, linked services, data flows, and parameterised pipelines across Bronze, Silver, and Gold Data Lake zones.

• Tested and certified Power BI dashboards for Claims Analytics, Fraud Detection, and Revenue Insights — verifying KPIs, drill-down logic, filters, and data accuracy against source SQL for 15+ executive reports.

• Performed defect root cause analysis (RCA) using Azure DevOps and JIRA, achieving average defect closure within 2 sprint cycles; zero critical data defects released to production in the last 6 months.

• Collaborated in Agile Sprint model with Data Engineering, DevOps, and Business Analyst teams; authored and reviewed BRD/FRS documents to derive 200+ test scenarios and test cases per sprint. ETL Tester & BI Reporting Tester Project : Costco Wholesale Corporation Azure SQL, Oracle, ADF, Databricks, Power BI, SQL Server, Azure DevOps (JUNE 2022- NOV 2023) Project: Retail Supply Chain & Sales Analytics Platform

• Led data migration validation from Oracle Data Warehouse to Azure SQL ecosystem, covering Sales, Inventory, Procurement, Customer Membership, and Supply Chain domains across 50M+ historical records.

• Executed source-to-target reconciliation for Oracle-to-Azure SQL migration; identified and reported 120+ data discrepancies in transformation logic, all resolved before UAT sign-off.

• Validated ETL transformation rules, data cleansing logic, and business derivations for Revenue, Margin, Inventory Aging, Stock Movement, and Supplier KPIs — ensuring 100% alignment with business specifications.

• Verified Power BI dashboards against legacy Cognos reports across 8 business domains; ensured pixel- perfect KPI parity and business logic compliance during Cognos-to-Power BI modernisation.

• Developed and maintained 50+ SQL automation scripts for regression validation and data quality checks, reducing sprint-on-sprint manual query effort by ~35%.

• Validated historical loads, incremental loads, and delta loads for Warehouse and Procurement pipelines; ensured zero data loss during cutover from legacy Oracle DW.

• Prepared Test Summary Reports, Traceability Matrices, and UAT Sign-off documents accepted by client stakeholders within agreed timelines.

• Logged, tracked, and closed defects in Azure DevOps maintaining defect density below 0.5 per test case and achieving 95%+ test case pass rate at UAT.

EDUCATION & CERTIFICATIONS

Bachelor of Commerce (B.Com) Kakatiya University, 2015

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