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Data Quality Assurance Engineer Jobs (NOW HIRING)

You will also mentor junior QA engineers and help shape the broader data quality practice across Abacus's data ecosystem, directly supporting regulatory and operational integrity. Your day to day

NAVA Software solutions is looking for a QA Engineer Details: QA Engineer Location: Houston, TX (2 ... Focused on Data Validation * Strong SQL skills * Any tools for data quality/ validation

Data QA Engineer

Bethesda, MD · On-site

$122K - $146K/yr

We are is looking for talented, enthusiastic senior data engineers who share our passion for big ... Qualifications Minimum Qualifications * 5+ years of work experience in QA, preferably in data or ...

Data QA Engineer

Bethesda, MD · On-site +1

$122K - $146K/yr

We are is looking for talented, enthusiastic senior data engineers who share our passion for big ... Qualifications Minimum Qualifications * 5+ years of work experience in QA, preferably in data or ...

Proficiency in Python for scripting and automation in data QA. * Experience with data analysis using Excel and handling large datasets. * Knowledge of data validation and quality checks. * Experience ...

QA Engineer

San Jose, CA · On-site +1

... assurance engineers ... Coordinate and collaborate with data quality control analysts and engineers in testing and ...

QUALITY ASSURANCE ENGINEER

Hollywood, MD · On-site

$75K - $90K/yr

This role leads root cause investigations, supports continuous improvement initiatives, and drives data driven trend analysis and response activities. The Quality Assurance Engineer partners closely ...

QA Engineer

Westminster, CO · On-site +1

$75K - $80K/yr

As a QA Engineer, you will be responsible for testing our software applications, data processes, reports, and dashboards, including validating data accuracy, calculations, filters, business logic ...

Moore is a data-driven constituent experience management (CXM) company achieving accelerated growth for clients through integrated supporter experiences across all platforms, channels and devices. We ...

The Senior QA Engineer will primarily lead quality assurance efforts within the software ... Recommend test approach, test environment requirements, and data strategies * Provide regular ...

Validate backend data using SQL and MySQL. * Log, track, and verify defects through resolution. * Collaborate with developers and QA teams to ensure software quality. * Support application releases ...

QA Engineer

Bohemia, NY · On-site

$70K - $105K/yr

The QA Engineer also works closely with cross-functional teams, suppliers, and customers while ... Data Device Corporation is an Affirmative Action/Equal Opportunity Employer and is committed to ...

QA Engineer

Bohemia, NY

$70K - $105K/yr

The QA Engineer also works closely with cross-functional teams, suppliers, and customers while ... Data Device Corporation is an Affirmative Action/Equal Opportunity Employer and is committed to ...

Full-time QA Engineer needed in Fort Worth, Texas. 5 years of experience required. Competitive ... Analyze data, lead team meetings, and develop solutions to eliminate or mitigate recurring issues.

Lead Data QA

Philadelphia, PA · On-site

$130K/yr

Collaborate with data governance, engineering, and architecture teams to embed QA best practices across the data lifecycle. Data Testing & Validation Design and implement automated test plans ...

Must have 5 years of experience in Quality Assurance, Quality Engineering, Electronics ... Analyze data, lead team meetings, and develop solutions to eliminate or mitigate recurring issues.

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Data Quality Assurance Engineer information

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$48

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How much do data quality assurance engineer jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for data quality assurance engineer in the United States is $48.54, according to ZipRecruiter salary data. Most workers in this role earn between $38.22 and $55.53 per hour, depending on experience, location, and employer.

What is the difference between Data Quality Assurance Engineer vs Data Analyst?

AspectData Quality Assurance EngineerData Analyst
Primary FocusEnsuring data accuracy, integrity, and quality through testing and validation processesAnalyzing data to identify trends, generate reports, and support decision-making
Skills & CertificationsKnowledge of data testing tools, SQL, data management, and quality standardsProficiency in data analysis tools, SQL, Excel, and visualization software
Work EnvironmentOften part of data engineering or QA teams within IT or data departmentsTypically within business intelligence, marketing, or analytics teams

While both roles work with data, the Data Quality Assurance Engineer focuses on validating and maintaining data quality, whereas the Data Analyst interprets data to provide insights. They often collaborate but serve different functions in data management and analysis processes.

What are the key skills and qualifications needed to thrive as a data quality assurance engineer?

To thrive as a Data Quality Assurance Engineer, you need strong analytical skills, attention to detail, and a background in computer science or a related field. Familiarity with SQL, data profiling tools, automation frameworks, and certifications like ISTQB are commonly required. Excellent problem-solving, communication, and collaboration skills set top performers apart in this role. These competencies are vital for ensuring data integrity, driving process improvements, and supporting business decision-making with reliable information.

What does a data quality assurance engineer do?

A Data Quality Assurance Engineer is responsible for ensuring the accuracy, consistency, and reliability of data within an organization. They design and implement tests, validation processes, and quality checks to identify and resolve data errors or inconsistencies. Their work helps maintain high-quality data standards, which is crucial for informed decision-making and effective business operations. Additionally, they collaborate with data engineers and analysts to establish data quality metrics and best practices.

Is a data quality assurance engineer still in demand?

Data Quality Assurance Engineers are in ongoing demand as organizations prioritize accurate and reliable data for decision-making. Skills in data validation, testing, and familiarity with tools like SQL and data quality platforms enhance employability in this field.

What are some common challenges faced by data quality assurance engineers when working with large datasets?

Data Quality Assurance Engineers often encounter challenges such as data inconsistency, incomplete records, and discrepancies across multiple data sources when handling large datasets. Ensuring data integrity requires meticulous validation and a strong understanding of both automated and manual testing techniques. Collaboration with data engineers, analysts, and business stakeholders is essential to identify root causes of quality issues and to implement effective solutions. Staying adaptable and detail-oriented helps address evolving data requirements and maintain high standards of data accuracy.
More about Data Quality Assurance Engineer jobs
What cities are hiring for Data Quality Assurance Engineer jobs? Cities with the most Data Quality Assurance Engineer job openings:
What states have the most Data Quality Assurance Engineer jobs? States with the most job openings for Data Quality Assurance Engineer jobs include:
Infographic showing various Data Quality Assurance Engineer job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 89% Full Time, 8% Part Time, and 2% Contract. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $100,970 per year, or $48.5 per hour.

Full-time

Medical, PTO

Posted 15 days ago


Job description

About Us
Abacus Insights is transforming how data works for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence.
We help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions-so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we're tackling big challenges in an industry that's ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows-and it's why we are leading the way.
Our innovation begins with people. We are bold, curious, and collaborative-because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable-those excited to leverage emerging technologies to enhance how we work-while keeping human insight, connection, and our clients at the center of every decision.
Ready to make an impact? Join us and let's build the future together.
About the Role
As a Senior Data Quality Engineer at Abacus Insights, you will own the accuracy, reliability, and compliance of healthcare data powering our cloud-native data management platform. This role requires deep expertise in data engineering, data quality architecture, and healthcare data domains. You will architect automated testing frameworks, lead data validation strategy, and partner with Engineering and Product leadership to maintain high-trust, high-quality datasets for health plan clients at scale. You will also mentor junior QA engineers and help shape the broader data quality practice across Abacus's data ecosystem, directly supporting regulatory and operational integrity.
Your day to day
  • Architect, build, and maintain enterprise-scale automated data quality validation frameworks, including rules engines, anomaly detection, and monitoring for completeness, conformity, integrity, and timeliness
  • Lead design and implementation of automated test strategies for complex healthcare data ingestion, transformation, and downstream application pipelines
  • Drive root cause analysis on high-impact data quality defects, own remediation strategy, and prevent recurrence through systemic process improvements
  • Define and evolve data quality strategy, standards, and best practices across pipelines, influencing tooling and process decisions org-wide
  • Partner directly with Engineering, Product, Project Management, Operations, and Connector Engineering leadership to translate business and compliance requirements into technical test plans, functional specifications, and validation logic
  • Lead review of software and data defect reports, identify systemic problem areas, and establish standards for reproducible issue documentation
  • Design and maintain advanced QA automation frameworks and dashboards using SQL, Python, Java, and cloud-native tooling
  • Lead system verification protocol design and represent QA in cross-functional architecture and design discussions
  • Conduct advanced data mining and profiling on client-specific and healthcare datasets to proactively surface quality risks at scale
  • Own documentation strategy including test plans, validation criteria, rule catalogs, and QA runbooks
  • Mentor and provide technical guidance to junior and mid-level QA engineers
  • Serve as an escalation point for internal and external data quality inquiries
  • Ensure data security and quality processes align with PHI handling, HIPAA, SOC 2, and Abacus governance requirements, and help evolve governance standards as the platform scales

What you bring to the team
  • Bachelor's or Master's degree in Computer Science, Information Systems, Data Analytics, or related technical field, or equivalent work experience.
  • 6-8+ years of experience in Data Quality Engineering and Data Engineering, with significant experience in healthcare technology or payer/provider environments
  • Expert-level SQL skills, including complex data manipulation, validation, and profiling at scale
  • Proven ability to lead data quality projects end-to-end.
  • Deep experience working with healthcare data types such as enrollment, medical claims, pharmacy claims, provider data, or non-traditional health and wellness datasets
  • Strong hands-on automation scripting expertise in Python or Java, with a track record of building reusable frameworks
  • Proven experience with cloud computing environments such as AWS (S3, EC2, SSM, Athena) and Databricks in production-scale settings
  • Demonstrated experience designing data integration workflows, ETL/ELT pipelines, data mapping strategy, and enterprise QA testing protocols
  • Track record of building and scaling automated QA applications, dashboards, or custom rule frameworks from the ground up
  • Proven ability to analyze complex, large-scale datasets, identify systemic quality issues, and drive actionable, measurable improvements
  • Experience mentoring engineers and influencing technical direction across teams
  • Excellent communication skills, with the ability to work cross-functionally, influence stakeholders, and operate independently with minimal oversight
  • Strong organizational and prioritization skills in a fast-paced, multi-project environment

What we would like to see, but not required
  • Deep exposure to Delta Lake, Spark, Airflow, dbt, or event-driven architectures
  • Advanced knowledge of schema evolution management (Parquet, Avro, ORC, JSON)
  • Experience leading data quality lifecycle management initiatives in large-scale cloud systems
  • Familiarity with Terraform, DevOps pipelines, CI/CD workflows, Git-based version control
  • Background in software debugging, system testing methodologies, or performance testing at an architectural level

Compensation: Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.
What you'll get in return
  • Unlimited paid time off - recharge when you need it
  • Work from anywhere - flexibility to fit your life
  • Comprehensive health coverage - multiple plan options to choose from
  • Equity for every employee - share in our success
  • Growth-focused environment - your development matters here
  • Home office setup allowance - one-time support to get you started
  • Monthly cell phone allowance - stay connected with ease

Our Commitment as an Equal Opportunity Employer
As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture-one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there's anything we can do to support that-big or small-please let us know.