QA Tester (ETL, Data Warehouse, SQL)

Kavya Narayanaswamy

**********************@*****.***

807-***-****

PROFESSIONAL SUMMARY

• Having 4 years of experience in ETL Testing, Data Warehouse Testing, Big Data Testing and BI Reporting Testing.

• Strong experience in validating ETL pipelines from Source to Target systems.

• Hands-on experience in Azure Data Factory, Data Bricks, SSIS.

• Good experience in Data Warehouse concepts like Fact Tables, Dimension Tables, Star Schema and Snowflake Schema.

• Experience in preparing Test Scenarios, Test Cases and Test Data based on BRD and Source to Target Mapping documents.

• Strong knowledge in Full Load, Incremental Load and CDC validations.

• Experience in validating complex transformations, aggregations, joins, lookups and business rules.

• Hands-on experience in SQL query writing for data validation and reconciliation.

• Experience in validating Fact and Dimension tables in enterprise Data Warehouses.

• Good exposure to Power BI and Tableau Report Testing.

• Experience in defect tracking and reporting using Jira and Azure DevOps.

• Strong analytical, troubleshooting and communication skills with Agile project experience.

TECHNICAL SKILLS

ETL Testing : ETL Testing, Data Warehouse Testing, Big Data Testing, BI Report Testing

Cloud Technologies : Azure Data Factory, ADLS

Databases : Oracle, SQL Server, Snowflake, PostgreSQL

Languages : SQL, Python, PySpark

Reporting Tools : Power BI

ETL Tools : SSIS, Azure Data Factory

Defect Tools : Jira, Azure DevOps, HP ALM

Methodologies : Agile Scrum

Version Control : Git

PROFESSIONAL EXPERIENCE

Worked as ETL Tester at Optimize RCM from Jan 2025 to May 2026.

Worked as Tester at Ventus Software from January 2022 to Dec 2024.

EDUCATION

Bachelor of Science (B.sc)

Maharani's Science college Bangalore

PROJECT 1

Project Name : Healthcare Data Integration & Clinical Analytics

Client : Athena healthcare

Role : ETL Tester

Environment : Azure Data Factory, Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Databricks (PySpark), Azure Synapse Analytics, Power BI, SQL Server

Project Description

The project was developed to modernize Athenahealth's healthcare analytics platform by integrating data from multiple Electronic Health Record (EHR), Electronic Medical Record (EMR), Practice Management, Claims, and Billing systems into Microsoft Azure. Azure Data Factory was used to ingest patient, provider, appointment, claims, billing, and clinical data into Azure Data Lake Storage Gen2. Azure Databricks (PySpark) performed data cleansing, validation, transformation, de-duplication, and healthcare business rule implementation. The processed data was stored in Azure Synapse Analytics using the Medallion Architecture (Bronze, Silver, and Gold) to support enterprise reporting, regulatory compliance, and operational analytics. Power BI dashboards were developed to provide insights into patient care, appointments, claims processing, provider performance, revenue cycle management, and healthcare operations.

Fact Tables: • Fact_Patient_Visits • Fact_Appointments • Fact_Claims

Dimension Tables: • Dim_Patient • Dim_Provider • Dim_Department • Dim_Diagnosis

• Dim_Date • Dim_Insurance

Roles & Responsibilities

• Reviewed BRD, FRD and Source to Target Mapping documents.

• Created Test Scenarios and Test Cases.

• Performed source to target data validation.

• Validated full load and incremental load processes.

• Performed record count validation and reconciliation testing.

• Validated Fact and Dimension tables.

• Tested joins, lookups and aggregation transformations.

• Executed SQL queries for validation.

• Performed duplicate, null and data integrity checks.

• Validated Power BI reports against Redshift data.

• Logged defects in Jira and tracked them to closure.

• Participated in Agile ceremonies and status meetings.

PROJECT 2

Project Name : Claims Data Warehouse

Client : Cigna Healthcare

Role : ETL Tester

Environment : Azure Data Factory, Azure Data Lake, SQL Server, Power BI, Oracle

Project Description

The project was developed to integrate claims, member and provider data into a centralized healthcare data warehouse. Data was extracted from multiple healthcare systems and transformed through Azure Data Factory before loading into the warehouse for reporting and analytics.

Fact Tables: Fact_Claims, Fact_Payments, Fact_Encounters

Dimension Tables: Dim_Member, Dim_Provider, Dim_Policy

Roles & Responsibilities

• Analyzed healthcare business requirements.

• Validated ETL workflows and data mappings.

• Performed source to target validation.

• Tested incremental and historical data loads.

• Validated CDC logic and updated records.

• Performed claim amount and payment reconciliation.

• Validated data quality rules and business transformations.

• Executed SQL queries for backend validation.

• Validated Power BI dashboards and KPI reports.

• Performed regression and defect retesting.

• Coordinated with developers and business teams.

• Prepared daily status reports.

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