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Data Quality Manager Jobs (NOW HIRING)

Novelis Corporate HQ

Data Quality Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Reporting to the manager of data governance, this role is responsible for establishing, operating, and configuring enterprise data quality standards, controls, and monitoring to ensure data is ...

TPC Wire and Cable

Data Quality Engineer

Macedonia, OH

$103K - $124K/yr

... CRM, analytics platforms, and customer-facing applications, while reducing operational ... Monitor data quality across core ISO-8000 data quality standards (i.e. completeness, accuracy ...

Vergence

Data Quality Lead

Carmel, IN

This role partners closely with Data Owners/Stewards, EDW Engineering, Governance, and Program Management to operationalize data quality standards, rules, metrics, monitoring, and remediation ...

TPC Wire and Cable

Data Quality Engineer

Macedonia, OH · On-site

$103K - $124K/yr

The Data Quality Engineer owns the implementation and continuous improvement of data quality across ... CRM, analytics platforms, and customer-facing applications, while reducing operational ...

The Reserves Network Inc

Data Quality Analyst

Wayne, PA · Hybrid

$29 - $39/hr

Opportunity to support a high-visibility enterprise Master Data Management (MDM) initiative * Work with cutting-edge data governance and data quality tools in a collaborative environment Join a ...

CAPTRUST

Data Quality Analyst

Raleigh, NC · On-site

Manage the data quality issue lifecycle from detection through remediation and verification, including triage, ownership, and root cause analysis * Promote data quality best practices, support ...

THE TILTED CIRCLE LLC

Data QA

Dallas, TX

Position: Data QA Location: Dallas, TX (Onsite) Duration: 12+ Months Contract W2 only Required ... Strong foundational knowledge of SQL, T-SQL, and relational database management systems (RDBMS)

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How much do data quality manager jobs pay per year?

As of Jun 20, 2026, the average yearly pay for data quality manager in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Quality Manager, and why are they important?

To thrive as a Data Quality Manager, you need a strong background in data management, data governance, and analytical skills, usually supported by a degree in information systems or a related field. Familiarity with data quality tools (such as Informatica, Talend, or SQL), data profiling techniques, and relevant certifications like CDMP are typically expected. Excellent communication, problem-solving abilities, and leadership skills help in collaborating with cross-functional teams and driving data quality initiatives. These skills ensure accurate, reliable data which is critical for informed business decision-making and regulatory compliance.

What is the average salary of a QA manager in the US?

The average salary of a Data Quality Manager in the US typically ranges from $80,000 to $120,000 annually, depending on experience, industry, and location. Many roles require strong analytical skills and familiarity with data management tools like SQL and data quality software.

What are the most common challenges a Data Quality Manager faces when implementing data governance initiatives?

Data Quality Managers often encounter challenges such as gaining cross-departmental buy-in, standardizing data definitions, and addressing inconsistent data entry practices. Successfully implementing data governance requires close collaboration with IT, business analysts, and leadership to align on data standards and processes. Additionally, managing change and ensuring ongoing user training are critical, as stakeholders may be resistant to new data policies or tools. Addressing these challenges proactively helps to build a culture of data ownership and accountability across the organization.

Is a data quality manager a good job?

A data quality manager is a valuable role responsible for ensuring the accuracy, consistency, and reliability of data within an organization. It typically requires strong analytical skills, knowledge of data management tools, and certifications such as CDMP or DAMA-DMBOK. The role offers opportunities for career growth in data governance and analytics fields.

What does a data quality manager do?

A data quality manager oversees the accuracy, consistency, and reliability of data within an organization. They develop data standards, implement quality control processes, and use tools like data profiling and validation to ensure data integrity for decision-making and compliance. Strong analytical skills and knowledge of data management software are essential for this role.

What is the difference between Data Quality Manager vs Data Analyst?

AspectData Quality ManagerData Analyst
Primary FocusEnsuring data accuracy, consistency, and integrity across systemsAnalyzing data to identify trends, patterns, and insights
Required SkillsData governance, quality control, database managementStatistical analysis, data visualization, reporting tools
CertificationsData Management certifications (CDMP, DAMA), SQLData analysis certifications (CAP, Microsoft Certified Data Analyst)
Work EnvironmentData governance teams, IT departments, enterprise systemsBusiness units, analytics teams, reporting departments

While both roles work with data, the Data Quality Manager focuses on maintaining data standards and quality assurance, whereas the Data Analyst interprets data to support business decisions. They often collaborate but serve different functions within organizations.

What is the salary for a quality manager?

The salary for a Data Quality Manager typically ranges from $70,000 to $120,000 annually, depending on experience, industry, and location. Professionals in this role often require strong analytical skills and familiarity with data management tools like SQL and data governance frameworks.
More about Data Quality Manager jobs
What cities are hiring for Data Quality Manager jobs? Cities with the most Data Quality Manager job openings:
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Data Quality Manager jobs near you
Infographic showing various Data Quality Manager job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.
Manager, Data Quality Engineering

Manager, Data Quality Engineering

Domino's

Ann Arbor, MI • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Domino's rating

4.8

Company rating: 4.8 out of 10

Based on 1,883 frontline employees who took The Breakroom Quiz

18th of 22 rated food delivery companies

Job description

Company Description
Domino's Pizza, which began in 1960 as a single store location in Ypsilanti, MI, has had a lot to celebrate lately: we're a reshaped, reenergized brand of honesty, transparency and accountability - not to mention, great food! In the rise to becoming a true technology leader, the brand is now consistently one of the top five companies in online transactions and 65% of our sales in the U.S. are taken through digital channels. The brand continues to 'deliver the dream' to local business owners, 90% of which started as delivery drivers and pizza makers in our stores. That's just the tip of the iceberg...or as we might say, one "slice" of the pie! If this sounds like a brand you'd like to be a part of, consider joining our team!
Job Description
As a Manager - Data Quality Engineering, you will lead the organization's data quality, quality engineering, and data analyst practice. This is a senior technical leadership role accountable for ensuring the reliability, trustworthiness, and operational excellence of data pipelines and data products across analytics, AI, and operational platforms.
You will partner closely with Data Engineering, Platform, Analytics, Product, and Business teams to embed quality-by-design into data pipelines, implement automated testing and observability, and run production data operations. The role combines proactive quality engineering with hands-on operational leadership-ensuring data issues are detected early, resolved quickly, and prevented from recurring at scale.
General Responsibilities:
Leadership, Team Development & Practice Building
  • Own the quality engineering practice end-to-end - vision, strategy, operating model, and roadmap. You are responsible for maturing QE from a support function into a core engineering discipline.
  • Partner with Data Engineering to ensure pipelines are resilient, observable, and aligned to business requirements.
  • Build, develop, and retain a high-performing team of quality engineers and analysts (onshore + offshore). Set clear expectations, provide regular feedback, and create growth paths for your team members.
  • Define and govern QE standards, processes, and KPIs - including automation coverage, cycle time, defect leakage, test effectiveness, and data validation coverage across all Lines of Business.
  • Establish a culture of engineering rigor and accountability - where quality is everyone's responsibility, not a gate at the end of the pipeline.
  • Create a knowledge repository that replaces tribal knowledge - enterprise test strategy, reusable patterns, and documented standards that scale beyond any individual.
  • Evaluate, adopt, and govern data quality and observability tools (build vs. buy) - e.g., Great Expectations, Soda, Monte Carlo, QuerySurge, or custom Databricks-native frameworks.
  • Build quality into data pipelines through preventive design, automated testing, and CI/CD quality gates.
  • Design and maintain automated checks for freshness, completeness, accuracy, validity, volume, and schema drift.
  • Establish enterprise data quality frameworks, scorecards, SLAs/SLOs, and standards for critical datasets.

Hands-On Technical Leadership
  • Stay close to the work by participating in design reviews, architecture discussions, and technical decision-making - ensuring quality is designed in, not tested in.
  • Guide the team in building automated data validation frameworks (Python, PySpark, SQL) covering data comparison, regression, BI report validation, and pipeline smoke tests.
  • Drive the embedding of quality gates into CI/CD pipelines - freshness, completeness, accuracy, validity, volume, schema drift, and business rule conformance checks before production deployment.
  • Architect and oversee data quality observability - dashboards, alerting, SLA-aligned thresholds, and escalation paths for engineers, product owners, and leadership.
  • Lead incident response for critical data quality issues - guide triage, RCA, post-mortems, and corrective actions. Reduce MTTR through automation and operational playbooks.
  • Selectively contribute hands-on to high-impact POCs, automation frameworks, and complex debugging - setting the technical standard through your own work when it matters most.

Cross-Functional Partnership
  • Partner with Data Engineering to ensure pipelines are resilient, observable, and aligned to business requirements.
  • Collaborate with Analytics, Product, and Business stakeholders to align quality metrics to business outcomes.
  • Support AI/ML initiatives by ensuring reliable, high-quality training and inference data.
  • Work with platform teams (Databricks, Azure, CI/CD tooling) to embed quality signals natively into orchestration and release workflows.

Qualifications
Must-have Skills & Experience
  • 8+ years in data engineering, analytics engineering, data quality, or data operations, with 2+ years in a lead, senior lead, or management role.
  • Demonstrated ability to build, mentor, and develop engineering talent - you know how to grow people, set expectations, and create accountability.
  • Strong technical judgment across data quality engineering, QA, and production data operations - you can evaluate designs, guide architecture decisions, and hold your team to high technical standards.
  • Proficiency in SQL and working knowledge of Python/PySpark - enough to review code, guide automation design, and contribute hands-on when needed. You don't need to be the best coder on the team, but you need to be technically credible.
  • Experience with modern cloud data platforms (Databricks, Delta Lake, Azure Data Lake, cloud data warehouses/lakehouses).
  • Experience embedding quality into CI/CD workflows - quality gates, automated regression, and release automation for data pipelines.
  • Experience leading or significantly contributing to incident response, RCA, and reliability improvement in production environments.
  • Ability to translate technical issues into clear business impact for executive and cross-functional audiences.

Nice to Have
  • Experience with data quality and observability tools (Monte Carlo, Great Expectations, Soda, QuerySurge, or custom frameworks).
  • Familiarity with orchestration and workflow tools (Control-M, Azure Data Factory, Databricks Workflows).
  • Experience supporting regulated or high-scale enterprise environments with production SLA governance.
  • Knowledge of data governance, metadata management, Unity Catalog, and data cataloging.
  • Experience with streaming data platforms (Kafka/Confluent) and schema management.
  • Exposure to dimensional modeling, data warehousing, and query performance tuning.
  • Experience with BI tools, semantic layers, or managing data product SLAs.

Education & Experience
BS/MS in Computer Science, Information Systems, Data/Analytics, or equivalent practical experience.
Additional Information
Benefits:
• Paid Holidays and Vacation
• Medical, Dental & Vision benefits that start on the first day of employment
• No-cost mental health support for employee and dependents
• Childcare tuition discounts
• No-cost fitness, nutrition, and wellness programs
• Fertility benefits
• Adoption assistance
• 401k matching contributions
• 15% off the purchase price of stock
• Company bonus
All your information will be kept confidential according to EEO guidelines.

What Domino's employees say

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About Domino's

Sourced by ZipRecruiter

Since 1960, we've grown from just one store to become the #1 pizza company in the world. To get there and continue to go above and beyond, it takes persistent passion, incredible vision, and bold thinking. It takes every one of our employees feeling like they have pizza sauce running through their veins. What's life like at Domino's Whatever your role at Domino’s, you’ll find life here is exciting, enormously fun, and always asks you to think on your feet. If you bring your passion, drive, and a purpose to perform, there are real growth opportunities across the brand. Many people find that what starts as a day job becomes a fulfilling career, surrounded by amazing people who make sure each new day tops the last. That’s what we mean by the power of possible. We are made better together In a Domino’s corporate job, our leaders work hard to create a level playing field where corporate team members can succeed, innovate, and above all, feel like they belong. See how different backgrounds make us better, and how your unique talents could power what’s possible in a Domino’s corporate career.

Industry

Food and beverage stores, real estate and food services and drinking places

Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

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