Data Quality Program Manager
Listed on 2026-02-13
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IT/Tech
Data Analyst, Data Warehousing, Data Security, Data Engineer
The Data Quality Program Manager is accountable for defining, leading, and continuously advancing the Bank’s enterprise Data Quality function. This role owns the strategy, operating model, and execution oversight for data quality across the organization, ensuring data is trusted, fit-for-purpose, and aligned with regulatory, risk, and business expectations.
Acting as the Bank’s senior authority on data quality, the Data Quality Program Manager provides enterprise leadership across governance, tooling, metrics, and issue management. The role partners closely with executive stakeholders across business, technology, risk, and compliance to embed data quality as a core organizational capability supporting the Bank’s data strategy, regulatory readiness, and analytics enablement. The position reports to the Director of Data Governance.
Key Responsibilities Enterprise Data Quality Strategy & Operating Model- Own and direct the Bank’s enterprise Data Quality Program, including vision, strategy, roadmap, and target-state operating model.
- Establish data quality as a formal, sustainable enterprise function with clear ownership and accountability.
- Define, approve, and maintain enterprise Data Quality Policies, Standards, and Procedures.
- Partner with Data Governance leadership to embed data quality into governance forums, operating models, and decision rights.
- Ensure alignment of data quality practices with regulatory requirements, internal controls, and risk management frameworks.
- Establish enterprise-wide data quality SLAs, KPIs, and KRIs and ensure consistent measurement across critical data domains.
- Provide executive-level oversight of data quality issues, including prioritization, remediation planning, and escalation.
- Lead data quality governance forums and working groups to drive accountability and cross-functional decision-making.
- Produce and present executive-level reporting on data quality health, trends, and risk exposure.
- Serve as the primary point of contact for audits, regulatory examinations, and data quality–related inquiries.
- Own the strategy and operating model for the Bank’s data quality and data observability tooling.
- Provide oversight for configuration of rules, thresholds, controls, and monitoring across enterprise datasets.
- Partner with Technology leadership to ensure scalable integration of data quality controls across platforms, pipelines, and architectures.
- Ensure alignment between data quality tooling, metadata management, and the enterprise data catalog.
- Act as the senior escalation point and subject matter authority for enterprise data quality matters.
- Partner with business leaders, data owners, and data stewards to define Critical Data Elements (CDEs) and quality expectations.
- Drive organizational adoption of data quality accountability through training, communication, and change management.
- Influence senior stakeholders to embed data quality controls into business processes, reporting, and analytics workflows.
- Build, lead, and develop the Data Quality function, including defining roles, responsibilities, and skill requirements.
- Establish standardized frameworks, methodologies, and best practices for data quality management.
- Mentor data quality resources and steward communities to mature enterprise data capabilities.
- Bachelor’s degree in Information Systems, Data Management, Business, Computer Science, or related field (advanced degree preferred).
- 8+ years of progressive experience in data quality, data governance, data management, or analytics, including enterprise or program leadership responsibilities.
- Demonstrated experience designing, leading, and scaling enterprise data quality programs, preferably in financial services or regulated environments.
- Deep understanding of data quality dimensions, data controls, and regulatory data expectations.
- Proven ability to lead cross-functional initiatives and influence senior-level stakeholders.
- Experience with modern data platforms and tooling (e.g., Snowflake, dbt, SQL, Python, Collibra,…
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