Data Governance Analyst II (Hybrid)

Key Responsibilities

• Supports and contributes to the implementation and ongoing enhancement of data governance policies, standards, and procedures.
• Executes data quality monitoring, issue management, and remediation activities with increasing ownership and accountability.
• Maintains and enhances data catalogs and metadata repositories (e.g., Atlan), ensuring accuracy, completeness, and usability.
• Leverages and helps implement automation and AI-assisted solutions to improve data quality monitoring, metadata management, and governance workflows.
• Partners directly with business data owners and stewards to define and document data elements, lineage, and usage.
• Facilitates discussions and working sessions to promote alignment on data definitions and governance practices.
• Supports and advocates for self-service analytics and AI-enabled data discovery, ensuring proper governance and control.
• Monitors and analyzes data governance metrics, including data quality trends, control effectiveness, and audit findings.
• Prepares and contributes to documentation for internal/external audits, regulatory exams, and risk assessments.
• Evaluates and supports governance controls for automated processes and AI-driven use cases, ensuring compliance with regulatory and internal standards.
• Contributes to enterprise initiatives such as data platform modernization, reporting enhancements, and regulatory change programs.
• Actively participates in cross-functional projects to embed governance into new systems, automated workflows, and AI-driven solutions.
• Identifies opportunities to improve processes through automation, standardization, and scalable data practices.

Qualification Requirements

• Bachelor’s degree in Information Systems, Business, Data Analytics, Risk Management, or a related field.
• Minimum 2 years of experience in data governance, data management, analytics, or a related field.
• Working knowledge of data governance principles, data quality management, metadata, and regulatory frameworks (e.g., DCAM, FFIEC, NIST).
• Experience with or exposure to data tools such as data catalogs (e.g., Atlan), data warehouses (e.g., Snowflake), transformation tools (e.g., dbt), or reporting platforms.
• Familiarity with or interest in data automation, AI/ML concepts, and AI-assisted analytics tools, with the ability to apply them in a governed environment.
• Strong analytical and problem-solving skills, with the ability to work independently and manage multiple priorities.
• Effective communication and collaboration skills, with experience working across technical and business teams in a regulated environment.