Compliance Data Steward
Compliance Data Steward
As the Compliance Data Manager, you will serve as the strategic lead and subject matter expert for the Compliance Data Domain, which encompasses all functions under the Compliance Division. You will act as the steward of the Bank’s core system for Compliance ensuring that data is accurate, accessible, and aligned with enterprise standards.
A key part of this role is to understand how Compliance data is created and used across the organization so that you drive the definition of the Vision and strategy for Workday, ensuring alignment with business objectives and stakeholder expectations.
You will spend a significant amount of time directly engaging with business contacts to understand data requirements, usage, and challenges to be addressed by the data strategy as well as with the Technology partner to create, prioritize, and refine requirements to ensure the development team is always working on the most valuable features
Key Responsibilities
Data Strategy & Governance
- Translate enterprise workforce strategies into actionable data management plans for the Compliance Data Domain.
- Lead new data initiatives by defining business cases, gathering requirements, and prioritizing projects across the domain.
- Establish and maintain processes aligned with Enterprise Data Policy and Standards for managing employee and contractor data.
- Oversee access and provisioning of Compliance data, including defining access controls, supporting data users, and ensuring compliance with Data Service Agreements and regulatory standards.
- Ensure that all Compliance data is governed in accordance with enterprise policies and controls.
Data Architecture
- Manage the definition of golden sources and systems of record for data in scope.
Data dictionary
- Support stakeholders in defining, validating, and maintaining business definitions for data elements.
- Accountable for data lineage and technical metadata for data elements within domain
- Identify need for changes in metadata within domain.
Data Quality
- Support stakeholders in developing and managing data quality controls for data within domain to satisfy consumer’s requirements.
- Oversee remediation of Data Quality issues through prioritizing issues to remediate; review and challenge remediation plans.
Demonstrated Skills
- Deep understanding of Compliance systems (e.g. Quantexa), and data.
- Fluency in data governance, data quality, and metadata management principles.
- Strong analytical and problem-solving skills with the ability to translate business needs into data solutions.
- Excellent communication and stakeholder engagement skills.
- Proven ability to lead cross-functional initiatives and manage competing priorities.
- Experience with regulatory and compliance requirements related to Banking industry
Qualifications
- 7+ years experience in Management role (Dir/ExecDir)
- 3+ years experience with Data Quality and Data Management
- Experience with data design, data audit, data governance and IT a plus
Bank’s data operating model comprises of enterprise-wide groups and federated data domains to drive accountability and management of data. The federated operating model ensures minimal overlaps and reduced handoffs of data attributes across the data lifecycle.
Federated data domains (data domains) are defined according to the various types of data originated and consumed by the enterprise (transactional, derived and master/reference), and in such manner that there are no unclaimed or overlapping data elements between two domains. Their definition and structure aim to support bank’s business activities and operations.
Data is clustered into federated domains with overall accountability and ownership for data quality, from origination to consumption. The Compliance Data Domain will manage data related to bank’s Compliance processes
Data Domains core responsibilities include definition and ownership of business use cases, serving as owners for and managing data within the domain (selected with view to exhaustively cover data within the enterprise with no overlaps), ensuring data satisfies the needs of data consumers, managing data quality assessments and remediation with source systems, expressing the data model and data definitions for the data elements within the domain, and participating in the enterprise data governance bodies.
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