What are the responsibilities and job description for the QA Lead ETL / Data position at Tanisha Systems, Inc.?
QA Lead ETL / Data
REMOTE / Work From Home
Salary – Market- DoE
We are looking for a QA Lead who is proficient in ETL/ Data testing to join our dynamic team who are at the forefront of enabling enterprises in Retail sectors. This engagement is the foundation of claims modernization program, delivering a Microsoft Fabric-based claims data platform and eligibility workflow application for five priority TPAs. The solution will standardize claims and eligibility data from multiple file formats and intake channels, automate manual validation processes, and provide curated Gold-layer data for claim creation, reporting, analytics, and future AI/ML initiatives. Phase 1 serves as the production foundation for scaling across broader network of 250 TPAs. The quality, accuracy, and scalability of the data platform, ingestion pipelines, and eligibility workflows established in this phase will directly impact future onboarding, operational efficiency, and business-critical claims processing across the enterprise. Effectively Communicate and collaborate with internal teams and customer and aligning to standard coding principles and guidelines.
Skills / Experience
Expected Outcome / What Success Looks Like – Successfully validate end-to-end claims and eligibility data pipelines across all five Phase 1 TPAs. Establish a robust QA framework covering data ingestion, transformation, Gold-layer validation, and eligibility workflow testing. Achieve high confidence in data quality through automated reconciliation, source-to-target validation, and regression testing. Support successful UAT execution and production deployment with minimal critical defects. Implement repeatable QA processes, test assets, and quality metrics that can scale to onboard additional TPAs in future phases. Phase 1 solution successfully deployed with QA sign-off and business acceptance. 95% test coverage across critical claims and eligibility workflows. Automated data validation and reconciliation processes established. Reduction in production data quality issues and post-release defects. Trusted, accurate Gold-layer datasets available for downstream consumption and analytics.
REMOTE / Work From Home
Salary – Market- DoE
We are looking for a QA Lead who is proficient in ETL/ Data testing to join our dynamic team who are at the forefront of enabling enterprises in Retail sectors. This engagement is the foundation of claims modernization program, delivering a Microsoft Fabric-based claims data platform and eligibility workflow application for five priority TPAs. The solution will standardize claims and eligibility data from multiple file formats and intake channels, automate manual validation processes, and provide curated Gold-layer data for claim creation, reporting, analytics, and future AI/ML initiatives. Phase 1 serves as the production foundation for scaling across broader network of 250 TPAs. The quality, accuracy, and scalability of the data platform, ingestion pipelines, and eligibility workflows established in this phase will directly impact future onboarding, operational efficiency, and business-critical claims processing across the enterprise. Effectively Communicate and collaborate with internal teams and customer and aligning to standard coding principles and guidelines.
Skills / Experience
- 6 years of experience in Data warehouse testing, ETL/DB testing and designing test plan/ strategy, and test cases
- 5 years of experience in leading Quality Assurance teams (Minimum of 5 team members) and customer interaction experience
- Strong experience in Fabric and Azure related testing experience like validating ADLS files, ADF Pipelines, Logic App, SSMS, performing aggregate checks along with source Vs target counts and data reconciliation
- 5 years of experience in writing complex SQL (t-SQL) queries and execute Stored Procs, Functions to test them
- Experience in integration testing, unit, functional and automation testing
- Should have Fabric and Azure related testing experience like validating ADLS files, ADF Pipelines, Logic App, SSMS, performing aggregate checks along with source Vs target counts and data reconciliation
- Should have strong experience testing Database centric application that involves complex data flows and transformations
- Experience in preparing quality reports and customer interaction
- Strong interpersonal skills to build and maintain productive relationships with team members
- Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
- Provides regular updates, proactive and due diligent to carry out responsibilities
- Secondary Skills / Good to have – Good at Power BI testing; Experience with Python scripting for data validation; Certification in software testing or quality assurance
- Lead a strategic claims modernization initiative: Help establish the quality foundation for this Microsoft Fabric-based claims platform, supporting 50,000 annual claims and laying the groundwork for onboarding 250 TPAs; Work with AI-powered accelerators at scale: Leverage WinWire''s WinAIDM – Data Ingestion Agent for automated source onboarding, schema detection, metadata extraction, and compliance tagging, significantly accelerating TPA integration
- Drive intelligent data quality engineering: Utilize WinAIDM – Data Quality Agent to automate validation rule generation, data reconciliation, and quality checks, enabling faster and more reliable testing outcomes; Accelerate transformation delivery: Gain exposure to WinAIDM – Data Transformation Agent and WinAIDM – Data Consumption/Reporter Agent, supporting streamlined data engineering, reporting, and analytics delivery across the modernization lifecycle
- Build the foundation for AI-driven claims operations: Ensure trusted Gold-layer data that powers claim creation, eligibility verification, reporting, analytics, and future AI/ML initiatives; Create enterprise-wide impact: The quality standards, testing framework, and governance processes established in Phase 1 will serve as the blueprint for scaling the platform across the broader TPA ecosystem and future modernization phases
Expected Outcome / What Success Looks Like – Successfully validate end-to-end claims and eligibility data pipelines across all five Phase 1 TPAs. Establish a robust QA framework covering data ingestion, transformation, Gold-layer validation, and eligibility workflow testing. Achieve high confidence in data quality through automated reconciliation, source-to-target validation, and regression testing. Support successful UAT execution and production deployment with minimal critical defects. Implement repeatable QA processes, test assets, and quality metrics that can scale to onboard additional TPAs in future phases. Phase 1 solution successfully deployed with QA sign-off and business acceptance. 95% test coverage across critical claims and eligibility workflows. Automated data validation and reconciliation processes established. Reduction in production data quality issues and post-release defects. Trusted, accurate Gold-layer datasets available for downstream consumption and analytics.