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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