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Manager, Data Quality

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Mastercard

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Location:
Canada , North York

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

Mastercard is seeking a highly skilled and motivated Manager, Data Quality to lead the development of scalable data quality workflows and drive continuous improvement for key products. The ideal candidate will bring a blend of technical expertise, leadership experience, and a passion for building automated, intelligent data validation systems that improve accuracy, reliability, and efficiency across the organization. This role requires strong collaboration across cross-functional teams, including Product, Data Engineering, Data Science, and Client Services. You will directly manage a team of analysts, mentor them, and set the quality strategy for merchant data used across Mastercard.

Job Responsibility:

  • Lead the design and implementation of scalable data cleansing, enrichment, and validation pipelines for Mastercard’s merchant data ecosystem
  • Develop data quality standards, metrics, scoring models, and dashboards to proactively measure and track quality improvements
  • Own the end-to-end data validation framework for Clarity, Smart Subscription, and related merchant intelligence products
  • Identify manual workflows in data cleansing, defect triage, validation, and enrichment
  • implement automated alternatives using Snowflake, Python, and AI/LLM-based solutions
  • Build automated rule engines, anomaly detection systems, and ML-enabled data validation checks to improve operational efficiency
  • Establish repeatable processes for data remediation, ensuring rapid resolution of data defects with minimal human intervention
  • Manage and mentor a team of data quality analysts, ensuring consistent delivery, upskilling, and performance excellence
  • Provide operational guidance, establish team KPIs, and integrate data quality objectives into overall product goals
  • Foster a culture of curiosity, continuous improvement, accountability, and innovation
  • Work closely with Data Engineering, Product, Data Science teams, and Engineering to identify upstream and downstream data quality issues
  • Serve as the subject-matter expert in merchant data to support client-facing teams and internal stakeholders
  • Translate business requirements into technical solutions and influence product roadmaps where data quality is a core component
  • Design, review, and optimize SQL transformations, Snowflake pipelines, and merchant data models
  • Contribute to version-controlled development using git, CI/CD tooling, and engineering best practices
  • Perform root cause analysis of data issues by analyzing ingestion pipelines, ETL/ELT logic, and data contracts
  • Implement data governance best practices, documentation standards, and metadata quality rules
  • Ensure processes follow Mastercard’s data protection, PCI, compliance, and privacy frameworks
  • Maintain comprehensive documentation of rule sets, workflows, lineage, and process changes

Requirements:

  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field
  • Team leadership/people management experience (analysts, data operations, or engineering functions)
  • In depth hands-on experience in data quality, data engineering, or analytics
  • Strong experience with SQL (Snowflake preferred), Python, git, and data modeling concepts
  • Proven ability to design and operationalize scalable data workflows and automation processes
  • Excellent communication skills—able to effectively collaborate with technical and non-technical stakeholders
  • Fast learner with a proactive, problem-solving mindset and strong attention to detail

Nice to have:

  • Experience working with merchant data, payment ecosystems, financial data, or transaction systems
  • Familiarity with AI/LLM models for cleansing, matching, enrichment, or anomaly detection
  • Experience with workflow orchestration (Airflow, ADF, DBT, Step Functions)
  • Knowledge of engineering reliability, observability, and data pipeline health monitoring
  • Experience building rule engines, classification systems, entity resolution models, or clustering algorithms
  • Ability to drive cross-team initiatives, influence without authority, and manage ambiguity

Additional Information:

Job Posted:
January 06, 2026

Employment Type:
Fulltime
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