ZipRecruiter

Log In

1

Data Qa Jobs (NOW HIRING)

ENE IT Consulting

Lead Data QA

Philadelphia, PA · On-site

$130K/yr

The Lead Data QA is responsible for defining and driving the overall Data Quality Assurance strategy for enterprise-scale data platforms. This role ensures that all data systems meet rigorous ...

1 point system

Data QA

New York, NY · Remote

$117K - $140K/yr

Cotiviti is seeking a QA Engineer with strong experience in testing data pipelines and validating large-scale data processing platforms. The ideal candidate will have hands-on expertise with ...

INSPYR Solutions

Data QA Analyst

Addison, TX · On-site

Data QA Analyst (Tax Focus) Location: Dallas TX Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S. Skillset / Experience: The Data QA Analyst is responsible for collecting ...

CYNET SYSTEMS

Data QA Engineer

Alpharetta, GA · On-site

$70/hr

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 ...

Abacus Insights

Senior Data QA Engineer

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

Ex Parte, Inc

Data QA Engineer

Bethesda, MD · On-site

$122K - $146K/yr

Qualifications Minimum Qualifications * 5+ years of work experience in QA, preferably in data or relevant space * Demonstrable knowledge, experience, skill, and proficiency with the following:

Ex Parte, Inc

Data QA Engineer

Bethesda, MD · On-site +1

$122K - $146K/yr

Qualifications Minimum Qualifications * 5+ years of work experience in QA, preferably in data or relevant space * Demonstrable knowledge, experience, skill, and proficiency with the following:

Charles Schwab Inc.

Data QA Engineer

Southlake, TX · On-site

$130K - $150K/yr

The Data QA Engineer will play a critical role in Schwab's Data Exchange space by helping ensure data applications are tested with accuracy, consistency, and release readiness. In this role, you'll ...

Charles Schwab

Data QA Engineer

Southlake, TX · On-site

The Data QA Engineer will play a critical role in Schwab's Data Exchange space by helping ensure data applications are tested with accuracy, consistency, and release readiness. In this role, you'll ...

State of Michigan

Data Quality Assurance Intern

Lansing, MI · On-site

$15.25 - $20.25/hr

Internship - Non Paid Job Number: 4301-21-Data Quality Intern Department: Health and Human Services ... Assurance Unit Maximum of 40 hours a week Required Education and Experience At the time of ...

next page

Showing results 1-20

All JobsData Qa Jobs

Data Qa information

See salary details

$44.5K

$129.7K

$177.5K

How much do data qa jobs pay per year?

As of Jul 30, 2026, the average yearly pay for data qa in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is the data QA role?

A Data QA (Quality Assurance) role involves reviewing and testing data to ensure accuracy, completeness, and consistency. Data QA professionals often use tools like SQL and data validation software to identify errors and verify data integrity within datasets or databases, supporting reliable data analysis and decision-making.

Will AI replace a data analyst?

AI can automate certain data analysis tasks, such as data cleaning and basic reporting, but it is unlikely to fully replace data analysts. Data analysts bring critical thinking, domain knowledge, and interpretative skills that complement AI tools, making their role essential for complex insights and decision-making. Proficiency in tools like SQL, Excel, and data visualization software remains important for the job.

What are top 3 skills for a QA analyst?

A QA analyst should have strong attention to detail, proficiency in testing tools and scripting languages, and good communication skills to document and report issues effectively. Knowledge of software development life cycle (SDLC) and familiarity with automation frameworks are also valuable. These skills help ensure software quality and efficient testing processes.

What is the difference between Data Qa vs Data Analyst?

AspectData QaData Analyst
Required CredentialsBasic understanding of testing tools, some certificationsDegree in data-related fields, certifications like Microsoft or SAS
Work EnvironmentQuality assurance teams, software testing environmentsData analysis teams, business intelligence settings
Employer & Industry UsageTech companies, software development firmsFinance, marketing, healthcare, and other industries
Common Search & ComparisonOften compared for data quality rolesMore focused on data insights and reporting

Data Qa professionals primarily focus on testing and ensuring data quality, often working within QA teams to validate data accuracy and integrity. Data Analysts, on the other hand, analyze data to generate insights, create reports, and support decision-making. While both roles work with data, Data Qa emphasizes quality assurance processes, whereas Data Analysts focus on data interpretation and analysis.

Is QA still in demand?

Quality Assurance (QA) roles, including Data QA, remain in demand as companies prioritize data accuracy and software quality. Skills in testing tools, scripting, and understanding data workflows are valuable, and demand is expected to grow with increasing reliance on data-driven decision-making.
More about Data Qa jobs
What cities are hiring for Data Qa jobs? Cities with the most Data Qa job openings:
What states have the most Data Qa jobs? States with the most job openings for Data Qa jobs include:
What job categories do people searching Data Qa jobs look for? The top searched job categories for Data Qa jobs are:
Data Qa jobs near you
Infographic showing various Data Qa job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Lead Data QA

ENE IT Consulting

Philadelphia, PA • On-site

$130K/yr

Other

Re-posted 4 days ago

Job description

Job Description e&e is seeking a Lead Data QA for a hybrid contract opportunity in Philadelphia, PA. The Lead Data QA is responsible for defining and driving the overall Data Quality Assurance strategy for enterprise-scale data platforms. This role ensures that all data systems meet rigorous standards for accuracy, performance, integration, security, and compliance.

The Lead Data QA will provide leadership and mentorship to a team of data QA analysts and testers, establish quality frameworks for ETL/ELT pipelines, and integrate automation within Azure Data Factory (ADF), Databricks, and Snowflake environments. The ideal candidate possesses a deep understanding of data engineering, automation frameworks, and regulatory data compliance (HIPAA, CMS) within modern cloud architectures. Responsibilities: Leadership & Strategy Define and own the enterprise Data QA strategy encompassing functional, non-functional, integration, and performance testing.

Lead and mentor a distributed team of Data QA professionals across multiple programs and data initiatives. Establish and maintain data quality SLAs, KPIs, and dashboards for critical datasets. 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, scripts, and frameworks for ELT/ETL pipelines. Validate complex payer datasets including claims, membership, provider, and clinical data. Conduct FHIR-based API testing for CMS interoperability and compliance standards.

Verify HEDIS measure calculations, healthcare quality metrics, and performance data accuracy. Log and track defects using appropriate QA tools; provide detailed feedback to engineering and architecture teams. Automation Strategy & Framework Develop and implement a data QA automation framework for Databricks (Delta Live Tables, Delta constraints) and ADF pipelines.

Utilize Great Expectations for reusable validation suites integrated into CI/CD workflows. Embed automated schema validation, reconciliation logic, and drift detection into data pipeline operations. CI/CD Integration Develop QA gates and automated quality checks within Azure DevOps pipelines for Databricks Jobs/DLT, SQL metadata, and ADF deployments.

Collaborate with DevOps and Engineering teams to embed QA automation into continuous integration and deployment processes. Technical Delivery Partner with ADF, Databricks, and Snowflake teams to ensure end-to-end data quality. Build and maintain automation frameworks leveraging Python, PySpark, and SQL.

Participate in code reviews, data model validation, and regression testing across environments. Work with business and data governance teams to identify, investigate, and remediate data quality issues. Performance & Compliance Design and execute automated load and stress tests for large-scale pipelines and dataflows.

Ensure all data QA processes align with HIPAA, CMS, and payer industry compliance standards. Support audits through proper documentation of QA processes, test results, and lineage verification. Requirements: Education: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.

Experience & Skills: 10+ years of experience in Data QA/Testing, with at least 5 years in a leadership capacity. Strong proficiency with Azure Databricks (Delta Lake, Delta Live Tables, Unity Catalog). Hands-on experience with Azure Data Factory pipelines, monitoring, and CI/CD deployment.

Advanced skills in Python, PySpark, and SQL for test automation. Experience with Great Expectations, Azure DevOps, and data quality automation frameworks. Familiarity with data governance, PII compliance, and enterprise data quality frameworks.

Proven success integrating QA practices into DevOps pipelines within cloud data environments. Excellent communication, leadership, and cross-functional collaboration abilities. Experience in Agile/Scrum environments is a plus.

Preferred Qualifications: Experience with HL7/FHIR data models beyond payer use cases. Knowledge of Lakehouse and medallion architecture Familiarity with BI validation using Power BI or Tableau. Understanding of data governance platforms (e.g., Collibra)

Prior experience designing data QA automation frameworks for pipelines and regression testing. Certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer.

Apply