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Data Quality Manager Jobs (NOW HIRING)

Figure

Data Quality Manager

San Jose, CA · On-site

They are seeking a Data Quality Manager to own data quality at Figure end-to-end, setting standards, building tooling, and leading the team that produces training data for their AI systems.

Figure

Data Quality Manager

San Jose, CA

$140K - $200K/yr

We are looking for a Data Quality Manager to own data quality at Figure end-to-end - setting the standards, building the tooling, and leading the team that produces the training data behind Helix and ...

Figure

Data Quality Manager

San Jose, CA · On-site

$140K - $200K/yr

We are looking for a Data Quality Manager to own data quality at Figure end-to-end - setting the standards, building the tooling, and leading the team that produces the training data behind Helix and ...

Procom Services

Data Quality Analyst

Dallas, TX

Application Development Project Management Quality Assurance Business/Systems Analysis ... Data Quality Analyst Job Details Responsibility : Define, Design, and Build Data quality management ...

Techwave

Data Quality Analyst - Senior Associate Experience: 3 - 5 yrs Location: Hyderabad Summary The Data ... Build and manage requirements traceability matrices, ensuring alignment from business requirements ...

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$31K

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How much do data quality manager jobs pay per year?

As of May 30, 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 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.

What does a Data Quality Manager do?

A Data Quality Manager is responsible for ensuring the accuracy, consistency, and reliability of an organization's data. They develop and implement data quality standards, monitor data integrity, and work closely with data analysts, IT teams, and business units to resolve data issues. Their goal is to ensure that data used for business decisions is trustworthy and meets regulatory and organizational requirements. This role often involves leading data governance initiatives and managing data quality improvement projects.

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.

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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What job categories do people searching Data Quality Manager jobs look for? The top searched job categories for Data Quality Manager jobs are:
Data Quality Manager jobs near you
Infographic showing various Data Quality Manager job openings in the United States as of May 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $97,145 per year, or $46.7 per hour.
Data Quality Manager

Data Quality Manager

Figure

San Jose, CA • On-site

Full-time

Posted 5 days ago

Job description

Job Summary:
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are seeking a Data Quality Manager to own data quality at Figure end-to-end, setting standards, building tooling, and leading the team that produces training data for their AI systems.
Responsibilities:
• Own data quality broadly at Figure — setting the strategy, standards, and operating model for how training data is produced, evaluated, and improved across all of our AI systems
• Own data quality metrics, including accuracy, consistency, rework rates, and guideline adherence across all labeling projects
• Define the standards, guidelines, QA methodologies, and audit processes for humanoid robot training data, effectively writing the playbook for an annotation discipline that doesn’t yet exist outside of a handful of frontier robotics labs
• Serve as a thought partner to the Helix team across all aspects of AI model development, helping shape what data we collect, how we evaluate it, and how data quality decisions feed into model behavior
• Develop onboarding and ongoing training programs for new and existing labelers
• Review edge cases and ambiguous annotations, driving resolution and guideline updates in collaboration with the ML team
• Partner with engineering to design and develop new internal tooling for annotation, QA, and data review
Qualifications:
Required:
• 8-10+ years of experience leading operational or data teams in a fast-paced environment, including hiring, performance management, and coaching
• Strong analytical and problem-solving skills, with the ability to diagnose quality issues and implement corrective actions
• Experience managing large-scale data quality or annotation operations
• Excellent written and verbal communication skills, especially when documenting standards and providing feedback using data
• Ability to manage competing priorities and time-sensitive deliverables under pressure
• High attention to detail and a strong quality-first mindset
• Proficiency in Google Workspace (e.g., Sheets) and operational or workflow management tools
Preferred:
• Experience working with robotics, autonomy, or sensor-derived data
• 10+ years of experience leading skilled teams operating complex or early-stage technology
• A passion for helping scale the deployment of learning humanoid robots
Company:
Figure is an AI robotics company that develops autonomous general-purpose humanoid robots. Founded in 2022, the company is headquartered in San Jose, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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