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Data Quality Manager Jobs in Quebec (NOW HIRING)

Utilize cloud-native data services, including Azure Storage, to optimize data management and scalability. * Implement and automate data quality checks using tools like DBT tests. * Implement and ...

Data Developer II

Sherbrooke, QC · On-site

CA$35.06 - CA$46/hr

Utilize cloud-native data services, including Azure Storage, to optimize data management and scalability. * Implement and automate data quality checks using tools like DBT tests. * Implement and ...

Ensure data quality, consistency, and completeness across all internal systems (ERP, PLM, CRM, eStore). * Act as the reference for product master data topics across Sustaining Engineering and ...

... data management. Data Analyst - AI focused in Hardware Manufacturing, Quality & Reliability Role Summary This role sits at the intersection of data analytics, hardware manufacturing, quality ...

The incumbent is also accountable for the accessibility, integrity, and quality of the required ... Ability to configure, use, and develop data management systems. * Ability to develop large-scale ...

Ensure data quality by driving and implementing robust data governance, automated testing, validation techniques, and lineage. * Metadata Management: Curate rich metadata in Unity Catalog and ...

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Data Quality Manager information

See Quebec salary details

$12

$44

$80

How much do data quality manager jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for data quality manager in Quebec is $44.46, according to ZipRecruiter salary data. Most workers in this role earn between $29.33 and $57.93 per hour, 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.

What job categories do people searching Data Quality Manager jobs in Quebec look for? The top searched job categories for Data Quality Manager jobs in Quebec are:
Infographic showing various Data Quality Manager job openings in Quebec 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 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $92,478 per year, or $44.5 per hour.

Assistant Manager, Data Quality & Business Analysis

IATA

Montreal, QC

Other

Re-posted yesterday


Job description

About the team you are joining

You will join the Turbulence Aware NextGen project team, a cross-functional group working to modernize IATA's turbulence data platform and deliver new data-driven capabilities for airlines. The team works closely with business, technology, vendor, and airline stakeholders to ensure the platform is reliable, scalable, and ready to support future products and services.

What your day would be like

In this role, your day would involve working closely with the Assistant Director and project stakeholders to support the Turbulence Aware NextGen platform migration and delivery of new data-driven features. You would review and document data quality requirements, analyze validation results, investigate data discrepancies, prepare reconciliation and testing evidence, and follow up on open issues with business, technical, vendor, and airline stakeholders. You would also help maintain key project documentation, support testing activities, contribute to dashboards and reports, and ensure that data quality, migration, and feature delivery activities are well documented and traceable.

Key responsibilities would 

 1.       Data Quality Governance & Control

         Support the definition and documentation of data quality requirements, including applicable standards, validation rules, business rules, and acceptance criteria, to help ensure the reliable and continuous operation of the Turbulence Aware NextGen platform.

         Support the Assistant Director in designing the Data Quality Control Module of Turbulence Aware NextGen.

         Support the design of the Quality Control Module and quality KPIs and dashboards for:

1.       Airline-provided EDR and ACARS data

2.       3rd party provided supplemental data

3.       Output datasets distributed to airline participants

         Identify, document, and investigate data anomalies, including root causes and define remediation actions.

         Support issue resolution with airlines, developers, infrastructure teams, and internal stakeholders.

         Document findings and support the preparation of audit-ready data quality reports.

2.       Data Migration Preparation & Reconciliation

         Support pre-migration data profiling and baseline validation.

         Assist in developing reconciliation frameworks for legacy vs. new platform outputs.

         Support validation of data completeness, consistency, timeliness, and accuracy before cutover.

         Track and document discrepancies, resolution actions, and sign-off criteria.

         Support cutover readiness assessments and post-migration stabilization reviews.

3.       Support for Turbulence Aware platform migration and new feature delivery

         Support development and validation of new revenue-generating features.

         Assist in defining acceptance criteria and validation metrics for nowcast, forecast, and alerting products.

         Support testing activities by preparing, documenting, and maintaining test scripts, and help track test execution progress.

         Help verify that deployed features meet defined quality, latency, and reliability standards.

         Assist in preparing documentation and dashboards for customers' onboarding and commercialization.

4.       Documentation & Governance

         Maintain comprehensive documentation, including:

o    Data dictionaries

o    Validation rules

o    Test plans and scripts

o    Reconciliation reports

o    Analytics feature specifications