ETL Testing & Data Warehouse QA Lead

RAVIKUMAR C – (Notice Period: Immediate Joiner)

**************@*****.*** +91-701******* linkedin.com/in/ravikumar-c-93200613b/

PROFILE SUMMARY

Over 8.10 years of experience in software testing with expertise in ETL, Data Warehouse, Databricks, Snowflake and Report Testing across diverse environments and industry domains.

Proficient in ETL Data Testing within MS SQL Server, Hive, Snowflake Cloud, Oracle, DB2, and Databricks platforms. Demonstrated experience in report testing using BOXI, Tableau, and Power BI, as well as ETL tools including Informatica, SAP BODS, and SSIS.

Comprehensive understanding of Data Warehouse concepts and Dimensional Modeling techniques, such as Star and Snowflake schemas. Skilled in developing complex SQL queries to apply business logic and validate result sets for ETL/BI mapping specifications.

Collaborated closely with Business Analysts to interpret business requirements and contributed to data-driven decision-making through in-depth data analysis.

Strong familiarity with Agile methodology and hands-on experience working within Scrum teams to deliver projects efficiently and on schedule.

Advanced testing capabilities encompassing Requirement Analysis, Test Design, Test Execution, Defect Logging, and Defect Tracking. Able to work independently and excel as part of a collaborative team.

WORK EXPERIENCE

May 2024 to September 2026: ValueMomentum Software Services Pvt Ltd

August 2021 to May 2024: Capgemini Technology Services

December 2020 to August 2021: LTI Technology Solutions

March 2019 to December 2020: Cognizant Technology Solutions

October 2017 to March 2019: Tata Consultancy Service

TECHNICAL SKILLS

Testing: ETL/DWH Testing

Database: Oracle, MSSQL, BD2, Databricks and Snowflake

ETL Tool: SSIS, Informatica and SAP Bods

Reporting Tool: Boxi, Power BI and Tableau

Web service: SoapUI

Test Management Tool: Jira, HP ALM

Operating System: Windows, Unix

PROFESSIONAL EXPERIENCE

Project: I

Project Name: Policy Fact Ingestion Client: Country Financial

Environment:

Databricks (PySpark, SQL), Delta Lake, Zena Scheduler

Role: Software Tester

Team Size: 2

Description:

End-to-end ETL testing was conducted for high-volume policy data ingestion originating from various source systems, including Dropbox and designated drop locations. The process was executed on the Databricks platform, leveraging PySpark scripts to ensure scalable data ingestion, transformation, and curation operations. This robust pipeline enabled dependable downstream analytics and comprehensive business reporting from the curated data layer.

The architecture implemented a medallion design, consisting of three distinct layers:

Landing Layer (Bronze Layer): Responsible for raw data ingestion from source systems.

EDL Core Layer (Silver Layer): Handles data cleaning, duplication check and validation of schema and data, transforming the ingested data into a reliable format.

EDL Curation Layer (Gold Layer): Provides business-ready, enriched data optimized for reporting and analytical purposes.

Responsibilities:

Analyzed requirements, business rules, and mappings to create test scenarios and cases for ingestion, transformation, and curation.

Wrote and ran SQL and PySpark queries to check data completeness, accuracy, schema, and transformation logic across all layers

Performed full ETL testing: initial load, incremental/delta loads, file ingestion, and PySpark job execution on Databricks

Validated Delta Lake tables for data quality, ACID properties, time travel, schema evolution, nulls, duplicates, and business rules

Collaborated with developments, data engineering, and business teams to resolve data issues quickly

Managed daily testing tasks, allocation, reviews, and stakeholder reporting

Supported UAT by preparing test data, clarifying defects, and assisting business users

Logged, tracked, and retested defects in Jira to improve pipeline quality and reduce production issues

Project: II

Project Name: DL Recommendation Generation Client: Morgan Stanley

Environment:

Informatica, DB2 and snowflake

Role: Software Tester

Team Size: 3

Description:

This project enables Morgan Stanley analysts to deliver relevant research to clients by analyzing their activity and recommending distribution lists. Analysts can then target those most interested in Morgan Stanley research.

Responsibilities:

Tested the full data loading process using the framework (source framework loading logic Snowflake target tables)

Wrote and executed SQL queries in Snowflake to verify data after framework loading

Checked that data loaded correctly: complete, accurate, no missing records, correct data types

Validated framework transformations (filtering, joining, aggregating client activity data) against mapping documents

Performed initial full load and incremental load (daily updates) testing in Snowflake

Verified Snowflake tables: row counts match source, no duplicates, no nulls in key fields, business rules applied correctly

Compared source data with Snowflake target using reconciliation SQL queries

Found issues in framework loading (wrong mapping, errors in loading logic, data mismatches) and reported in JIRA

Worked with developers to fix framework bugs and Snowflake data problems

Supported UAT by preparing Snowflake test data, showing results to business users, and helping resolve questions

Project: III

Project Name: Wyndham Genesis Shell Integration Client: Wyndham

Environment:

Informatica Cloud, Oracle

Role: Software Tester Team Size: 2

Description:

Wyndham, a US-based hotels and resorts company, aimed to integrate external systems with OFSLL data via inbound and outbound interfaces. Outbound files from OFSLL were sent to Oracle-MFT and uploaded to vendor FTPs using MoveIT. For inbound processing, vendors placed files in secure SFTP locations, which ETL jobs loaded into Oracle work tables.

Responsibilities:

Reviewed requirement specification documents to gain insight into data flow and business rules.

Conducted validation of the entire ETL data flow across multiple layers.

Verified source data loading from various origins to the Landing layer, ensuring correctness and completeness.

Maintained data quality by enforcing business rules at each layer.

Assessed transformation logic (including Filter, Aggregator, Router, Lookup, Expression, Sorter, Sequence Generator, and Joiner) based on mapping documentation.

Developed and executed complex SQL queries to confirm data accuracy and completeness across layers.

Executed initial full load as well as incremental load testing procedures.

Monitored ETL job execution status, managed exception handling, and reviewed error logs.

Authored and performed comprehensive test cases.

Provided daily testing status updates to the team.

Collaborated with Business Analysts and Developers to address data and functional issues.

E D U C A T I O N

M.C.A., (Master of Computer Applications) from Anna University.

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