Job Description
The Director of Data Quality (DQ) and Master Data Management (MDM) Operations is responsible for ensuring that Cetera's critical data is trusted, timely, and fit for purpose as it flows through the enterprise data supply chain into the integrated data platform. This role leads the execution of Data Quality and Master Data Management capabilities, working in close partnership with Data Architecture and Data Trust to deliver high quality, well structured data that supports analytics, AI, operational use cases, and the future growth of the firm.
Reporting to the Managing Director, Head of Data, this leader operates as part of an integrated data leadership team, where architecture, quality, trust, and stewardship are applied in a coordinated and orchestrated way for business critical data domains. The role is accountable for turning standards, definitions, and ownership into operational outcomes that enable trusted data at scale.
Key Responsibilities
Enterprise Data Quality (DQ)
Own and operationalize the enterprise DQ framework in close collaboration with Data Architecture and Data Trust, ensuring alignment across standards, definitions, and operational processes.
Partner with business stakeholders, Data Architecture, Data Trust, IT, and Analytics to define and implement business data quality rules that support enterprise data models and downstream consumption.
Lead remediation processes and enforce SLAs, working with data owners and upstream teams to resolve issues at the source and prevent recurrence.
Run a proactive data quality improvement program, focused on:
o identifying systemic issues
o resolving root causes
o preventing recurrence
Oversee DQ monitoring, scorecards, and issue transparency across priority domains and systems.
Partner on cross-functional quality initiatives (e.g., sponsor data feed quality programs) to improve upstream and third party data quality.
Master Data Management (MDM)
Lead MDM operations as an integrated component of the broader data quality and data trust ecosystem, ensuring that mastered data aligns with enterprise models, definitions, and business ownership.
Partner with Data Architecture to ensure MDM rules, hierarchies, and workflows support consistent, scalable data structures across the integrated data platform.
Lead MDM operations, including stewardship workflows, mastering rules, and lifecycle management.
Ensure consistent, governed mastering of enterprise domains, including:
o Financial Advisor
o Client
o Securities
o Rep Codes
o Product
o Sponsor
o and additional domains as business needs evolve
Define and oversee match/merge and survivorship logic, hierarchies, and validation rules that ensure mastered data is accurate, consistent, and usable.
Work closely with Data Trust and business data owners to ensure stewardship workflows reflect agreed ownership, definitions, and accountability.
Enable and support business users and data stewards in effectively working with mastered data.
Data Operations Leadership
Build, lead, and scale a DQ and MDM Operations team, including managers and analysts.
Establish clear operating rhythms, prioritization, and performance measures for data operations.
Partner closely with:
o Data Architecture (alignment with enterprise modeling standards, MDM Design and integration, DQ-by-design)
o Data Trust (ownership, definitions, evidence)
o IT (platforms, integrations)
o BI & Analytics (consumability and issue feedback loops)
o Business stakeholders and data owners
Act as a senior point of escalation for critical data quality and mastering issues impacting reporting, analytics, and business operations.
Ensure that data quality, mastering, and remediation activities are aligned to enterprise priorities and platform delivery needs, rather than optimized in isolation.
DQ & MDM Technology Enablement
Serve as the business owner and informed leader for DQ and MDM technology solutions, bringing practical experience with industry leading platforms and tools.
Partner with IT and Data Architecture to evaluate, implement, and evolve DQ and MDM technologies that support enterprise scale, automation, and integration with the data platform.
Apply a pragmatic, value driven approach to leveraging analytics, automation, and advanced AI capabilities to:
o Improve (proactive) detection and prevention of data quality issues
o Enhance stewardship workflows and prioritization
o reduce manual effort and cycle time in remediation and mastering processes
Continuously assess emerging capabilities in the DQ and MDM technology landscape and incorporate them where they meaningfully improve data trust, speed, or operational efficiency.
Qualifications
10+ years of experience in data management, with 5+ years in senior leadership roles spanning Data Quality, Master Data Management, or data operations in a complex, regulated environment.
Strong experience owning and operating DQ and/or MDM platforms in partnership with IT, including translating tool capabilities into operational processes and measurable outcomes.
Proven ability to translate business requirements into operational data rules, workflows, and outcomes.
Experience applying or enabling advanced analytics, automation, or AI driven techniques to improve data quality, stewardship effectiveness, or scalability (hands on development not required).
Experience working with external 3rd party firms to define/deploy data quality framework and resolve data quality issues.
Demonstrated success leading teams and driving cross functional accountability.
Experience in financial services or similarly regulated industries strongly preferred.
#LI-Hybrid
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: RTX1a6d2c
- Position Id: 6346
- Posted 3 hours ago
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