Inovalon

Healthcare

QualityEngineer-DataQuality&TestDataManagement

$95–135k ~AI est. United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Quality Engineer - Data Quality & Test Data Management at Inovalon. Skills: Data Quality, Test Data Management, SQL, Data Validation. Own and maintain test data strategies. Create, curate, and validate test datasets”

Industry & Context.

Healthcare
Problems you'll solve

Analytical thinking; Root cause analysis

Eligibility Requirements

Authorized to work in US

What They're Looking For.

Must Have

4-8 years experience in software quality assurance, Emphasis on data validation and testing, Complex SQL queries for validation and analysis, Testing data extractions, reports, ETL pipelines, or data migrations, Experience working in Agile Scrum teams, Understanding of SDLC, Agile workflows, and defect management, High attention to detail, Analytical thinking skills, Communicate data quality risks clearly

Nice to Have

Experience in healthcare, Experience in regulated environments, Experience in data-intensive platforms, Familiarity with healthcare data concepts, Familiarity with compliance considerations, Familiarity with reporting requirements, Validating large or complex datasets, Exposure to automation-friendly test design, Experience using AI-assisted tools

What You'll Do.

Own and maintain test data strategies

and validate test datasets

Ensure test data accuracy and alignment

Partner with engineering to mitigate risks

Validate data extractions

Test and reconcile data for reports

Test and reconcile data for feeds

Test and reconcile data for analytics

Perform data reconciliation testing

Design and execute test plans for data migrations

Validate migrated data preservation

Use advanced SQL queries for validation

Support root-cause analysis

Validate schema changes

Validate data model updates

Validate database-level impacts

Participate in Agile Scrum team

Contribute to sprint planning

Contribute to backlog refinement

Contribute to stand-ups

Contribute to reviews

Contribute to retrospectives

Define data-related acceptance criteria

Identify data quality risks

Communicate data quality risks

Create data-centric test plans

Create data-centric test cases

Leverage AI-assisted tools for test scenarios

Improve coverage for complex data sets

Collaborate to transition data tests to automation

Document and communicate data defects

Identify recurring data issues

Recommend systemic improvements

Contribute to improvements in data quality standards

Contribute to improvements in QA practices

How You'll Work.

Team & Collaboration

Agile Scrum team; Software Engineers; Quality Engineers; Quality Analysts; Product stakeholders; Engineering teams

Communication Scope

Communicate risks

Process & Methodology

Agile, Scrum

Full Job Description

Inovalon was founded in 1998 on the belief that technology, and data specifically, would empower the transformation of the entire healthcare ecosystem for the better, improving both outcomes and economics. At Inovalon, we believe that when our customers are successful in their missions, healthcare improves. Therefore, we focus on empowering them with data-driven solutions. And the momentum is building. Together, as ONE Inovalon, we are a united force delivering solutions that address healthcare’s greatest needs. Through our mission-based culture of inclusion and innovation, our organization brings value not just to our customers, but to the millions of patients and members they serve. Role Overview We are seeking a Quality Engineer with a strong data and technical background to focus on test data management, SQL‑driven validation, and data quality assurance for a cloud‑native healthcare application. This role is essential to ensuring the accuracy, consistency, and integrity of data used for reporting, analytics, integrations, and data migrations/conversions. This position operates as a core member of an Agile Scrum team, working closely with Software Engineers, Quality Engineers, Quality Analysts and product stakeholders to validate complex data flows end‑to‑end. The ideal candidate combines traditional QA discipline with deep analytical thinking, strong SQL skills, and a clear understanding of how healthcare data quality impacts customers, regulatory outcomes, and business trust. Key Responsibilities Test Data Management Own and maintain test data strategies that support functional testing, regression testing, performance testing, reporting validation, and data migrations. Create, curate, and validate high‑quality test datasets that reflect real‑world healthcare scenarios, edge cases, and historical data patterns. Ensure test data remains accurate, reusable, and aligned with evolving schemas and business rules. Partner with engineering to identify and mitigate risk

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