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 risks related to shared databases and cross‑functional data dependencies.

Data Quality & Validation Testing

Validate data extractions, transformations, and loads (ETL) used for reporting, downstream feeds, and analytics.
Test and reconcile data used in:
- Operational and regulatory reports
- Customer‑facing reports
- Internal analytics and dashboards
Perform data reconciliation testing to ensure completeness, accuracy, and consistency across systems.

Data Migration & Conversion Testing

Design and execute test plans for data migrations and conversions, validating both historical and in‑flight data.
Confirm that migrated data preserves:
- Referential integrity
- Business rules and calculations
- Regulatory and healthcare data requirements
Partner with engineering and stakeholders to validate pre‑ and post‑migration data states.

SQL & Technical Analysis

Use advanced SQL queries to validate data correctness, detect anomalies, and identify data quality issues.
Independently analyze data issues and support root‑cause analysis in collaboration with engineering teams.
Validate schema changes, data model updates, and database‑level impacts as part of sprint delivery.

Agile & Scrum Team Participation

Act as a full participant in an Agile Scrum team, contributing to sprint planning, backlog refinement, stand‑ups, reviews, and retrospectives.
Ensure data‑related acceptance criteria are clearly defined and testable before work enters a sprint.
Identify data quality risks early in the sprint lifecycle and communicate them clearly to the team.

Test Design & Automation Readiness

Create data‑centric test plans and test cases that are structured, repeatable, and automation‑ready.
Leverage AI‑assisted tools to help generate test scenarios, identify edge cases, and improve coverage for complex data sets (with appropriate validation and oversight).
Collaborate with Quality Engineers to transition suitable data tests into automated pipelines.

Defect Management & Continuous Improvement

Clearly document and communicate data defects, including reproduction queries, expected vs. actual results, and data impact.
Identify recurring data issues and recommend systemic improvements to prevent future defects.
Contribute to improvements in data quality standards, metrics, and QA practices.

Required Qualifications

4–8 years of experience in software quality assurance with a strong emphasis on data validation and testing.
Strong SQL skills, including the ability to write complex queries for validation and analysis.
Hands‑on experience testing data extractions, reports, ETL pipelines, or data migrations.
Experience working as part of Agile Scrum teams.
Strong understanding of SDLC, Agile workflows, and defect management processes.
High attention to detail and strong analytical thinking skills.
Ability to communicate data quality risks clearly to technical and non‑technical stakeholders.

Preferred Qualifications

Experience in healthcare, regulated environments, or data‑intensive platforms.
Familiarity with healthcare data concepts, compliance considerations, or reporting requirements.
Experience validating large or complex datasets across shared databases.
Exposure to automation‑friendly test design for data pipelines.
Experience using AI‑assisted tools to support test case creation or data analysis.

This position is not eligible for immigration sponsorship (e.g. H-1B, TN, or E-3). Applicants must be authorized to work in the United States as a condition of employment. (This is only applicable for US-based positions)

If you don’t meet every qualification listed but are excited about our mission and the work described, we encourage you to apply. Inovalon is most interested in finding the best candidate for the job, and you may be just the right person for this or other roles.

By embracing inclusion, we enhance our work environment and drive business success. Inovalon strives to provide equal opportunities to the communities where we operate and to our clients and everyone whom we serve. We endeavor to create a culture of inclusion in which our associates feel empowered to bring their full, authentic selves to work and pursue their professional goals in an equitable setting. We understand that by fostering this type of culture, and welcoming different perspectives, we generate innovation and growth.

Inovalon is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirement.

To review the legal requirements, including all labor law posters, please visit this link

To review the California Consumer Privacy Statement: Disclosures for California Residents, please visit this link

Quality Engineer - Data Quality & Test Data Management