1

Data Quality Engineer Jobs (NOW HIRING)

Informatica Data Quality Developer

Tampa, FL · On-site

$48.50 - $63.75/hr

Informatica Data Quality Developer Informatica Data Quality Developer - 2 (Tampa or Dallas) - 8+ years of IT experience in developing high-performance, high-volume data engineering and warehouse ...

Senior Data Engineer - Quality

Chicago, IL · On-site

$100K - $150K/yr

The Senior Data Engineer - Quality is a hands-on technical role responsible for designing and building robust, scalable, end-to-end testing frameworks for modern data pipelines. This role focuses on ...

Senior Data Engineer - Quality

Chicago, IL · Hybrid

$100K - $150K/yr

The Senior Data Engineer - Quality is a hands-on technical role responsible for designing and building robust, scalable, end-to-end testing frameworks for modern data pipelines. This role focuses on ...

Job Title: Quality Engineer Location: Plano, TX Duration: Long Term Contract Requirements ... Strong knowledge of Snowflake Data Warehouse, including data validation, testing methodologies, and ...

next page

Showing results 1-20

Data Quality Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do data quality engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for data quality engineer 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 are some common challenges faced by Data Quality Engineers in their role?

Data Quality Engineers often encounter challenges such as integrating data from diverse sources, identifying and resolving inconsistencies or gaps in large datasets, and ensuring ongoing compliance with data governance policies. They regularly work with other data professionals to define data quality metrics, establish validation rules, and automate data cleansing processes. Problem-solving and adaptability are key, as you may have to address unexpected data issues that impact critical business operations. Successfully overcoming these challenges is vital for enabling organizations to make data-driven decisions with confidence.

What are the key skills and qualifications needed to thrive in the Data Quality Engineer position, and why are they important?

To thrive as a Data Quality Engineer, you need a strong background in data analysis, data management, and database technologies, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, ETL platforms, data profiling tools, and certifications such as CDMP or from DAMA International are highly valuable. Excellent problem-solving skills, attention to detail, and strong communication help you collaborate effectively with cross-functional teams. These skills ensure that data systems are reliable, accurate, and support business goals across an organization.

What is a Data Quality Engineer job?

A Data Quality Engineer ensures the accuracy, consistency, and reliability of data within an organization. They develop and implement data quality frameworks, perform data profiling, create validation rules, and monitor data pipelines to detect anomalies. Their role often involves working with databases, ETL processes, and data governance teams to maintain high data integrity. Strong analytical skills, proficiency in SQL, and knowledge of data validation tools are essential for this role.

More about Data Quality Engineer jobs
What cities are hiring for Data Quality Engineer jobs? Cities with the most Data Quality Engineer job openings:
What states have the most Data Quality Engineer jobs? States with the most job openings for Data Quality Engineer jobs include:
Infographic showing various Data Quality Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Sr. Data Quality Engineer (40_2026.1)

Sr. Data Quality Engineer (40_2026.1)

Affinity Solutions

New York, NY

$130K - $145K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 4 days ago


Job description

Affinity Solutions is the leading consumer purchase insights company. We provide a complete view of U.S. and U.K. consumer spending, across and between brands, via exclusive access to fully permissioned transaction data from over 100 million consumers. Our proprietary AI technology, Comet, transforms these purchase signals into actionable insights for business and marketing leaders to drive optimal outcomes and build lasting customer relationships. Visit www.affinitysolutions.com to discover how were shaping the future of consumer purchase insights.

About Your Role:

Affinity Solutions is seeking an accomplished Senior Data Quality Engineer to spearhead critical initiatives ensuring the accuracy, reliability, and compliance of Affinity's enterprise data ecosystem. In this strategic role, you will architect and implement sophisticated data quality frameworks, optimize data pipelines, and partner with cross-functional teams to deliver trusted, high-performance data solutions that drive business value. The ideal candidate combines deep technical expertise with proven leadership capabilities and a strategic vision for advancing data quality and governance maturity.

Your Responsibilities:

  • Data Quality Strategy & Leadership
    • Establish and enforce enterprise-wide data quality standards, frameworks, and best practices aligned with organizational objectives
    • Lead comprehensive data quality initiatives to monitor, validate, and enhance data accuracy, completeness, consistency, and timeliness across all systems
    • Design and implement automated data quality validation, profiling, and anomaly detection mechanisms
    • Define and track key data quality metrics and SLAs to measure and improve data reliability
    • Implement data quality gates and validation checkpoints throughout the data lifecycle
  • Data Governance & Compliance
    • Develop and maintain comprehensive metadata repositories, data dictionaries, and data lineage documentation to ensure transparency and traceability
    • Ensure strict adherence to data privacy regulations (GDPR, CCPA, HIPAA) and industry compliance standards
    • Implement and enforce robust security measures including data encryption, masking, tokenization, and role-based access controls
    • Participate in data governance committees and contribute to policy development
  • Cross-Functional Collaboration & Mentorship
    • Partner closely with data scientists, analytics engineers, platform engineers, and business stakeholders to deliver reliable, fit-for-purpose data solutions
    • Provide technical mentorship and guidance to junior and mid-level engineers, fostering a culture of excellence in data quality
    • Conduct code reviews and promote engineering best practices across the data organization
    • Translate complex technical concepts for non-technical stakeholders
  • Innovation & Continuous Improvement
    • Monitor and evaluate emerging technologies, tools, and methodologies in data quality, observability, and governance
    • Identify opportunities for process optimization and technical debt reduction
    • Lead proof-of-concept initiatives to validate new technologies and approaches
    • Drive strategic recommendations to enhance data reliability, efficiency, and organizational data maturity

Your Qualifications:

  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical field; Master's degree preferred
  • 5+ years of progressive experience in data quality engineering, data governance, or data platform engineering
  • Demonstrated track record of implementing enterprise-scale data quality solutions
  • Proven experience leading technical initiatives and mentoring engineering teams
  • Core Technical Competencies:
    • Expert-level proficiency in SQL and query optimization techniques
    • Advanced programming skills in Python, including libraries for data processing (Pandas, NumPy, PySpark)
    • Strong understanding of distributed computing frameworks (Apache Spark, Hadoop ecosystem)
    • Deep expertise in data modeling methodologies (dimensional modeling, data vault, 3NF)
    • Comprehensive knowledge of ETL/ELT design patterns and data integration strategies
  • Platform & Tools:
    • Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure)
    • Proficiency with modern cloud data warehouses (Amazon Redshift, Google BigQuery, Snowflake)
    • Experience with data quality and observability tools (Great Expectations, Soda Core, Monte Carlo, or similar)
    • Familiarity with workflow orchestration tools (Apache Airflow, Prefect, Dagster)
    • Knowledge of data cataloging and governance platforms (Datahub, Openmetadata, Alation, or similar)
    • Version control systems (Git) and CI/CD practices
  • Data Governance & Compliance:
    • Working knowledge of data privacy regulations (GDPR, CCPA) and compliance frameworks
    • Understanding of data security principles and implementation of access controls
    • Experience with metadata management and data lineage tracking

Salary Range: : $130,000$145,000 annually (commensurate with experience and qualifications)

Office Hours: 9am 5:30pm

Benefits:

As a full-time member of our team, your benefits will include generous company contributions for medical, dental, and vision. In addition to company-paid holidays, wellness time off, and other wellness benefits, you will also receive company-paid life insurance and the option to enroll in a 401K Plan with employer match. We encourage work/life balance with unlimited vacation days, available after 90 days of employment, as well as employee discounts and professional development opportunities.