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Key Responsibilities and Required Skills for a Governance Analyst Assistant

💰 $55,000 - $75,000

Data & AnalyticsGovernanceComplianceEntry-LevelTechnology

🎯 Role Definition

The Governance Analyst Assistant is a crucial entry-level role supporting the Data Governance team in establishing and enforcing enterprise-wide data policies, standards, and processes. You will be instrumental in improving data quality, managing critical data assets, and fostering a data-driven culture across the organization. This position works closely with data stewards, business analysts, and IT teams to transform data from a simple byproduct into a reliable and strategic enterprise asset. If you are passionate about organization, quality, and the power of well-managed data, this role is your gateway to a thriving career.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Recent Graduate (MIS, Computer Science, Business)
  • Junior Business Analyst or Data Analyst
  • IT Support or Helpdesk Specialist

Advancement To:

  • Data Governance Analyst
  • Data Quality Analyst
  • Data Steward or Metadata Analyst

Lateral Moves:

  • Business Intelligence (BI) Analyst
  • Compliance Analyst
  • Master Data Management (MDM) Specialist

Core Responsibilities

Primary Functions

  1. Actively assist in the development, documentation, and implementation of enterprise-wide data governance policies, standards, and procedures.
  2. Support the data stewardship community by facilitating meetings, documenting decisions, and tracking action items to ensure accountability and progress.
  3. Maintain and enrich the enterprise data dictionary and business glossary, ensuring clear, consistent, and accessible definitions for critical data elements.
  4. Execute data quality profiling and analysis using various tools to identify anomalies, inconsistencies, and data quality issues.
  5. Develop and maintain data quality dashboards and reports to monitor key data quality metrics and communicate trends to stakeholders.
  6. Participate in the investigation and root-cause analysis of data quality issues, collaborating with business and IT teams to drive remediation efforts.
  7. Help document and map data lineage, tracing data flows from source to consumption to enhance transparency and trust in data.
  8. Support the classification of data assets according to sensitivity, criticality, and regulatory requirements (e.g., PII, PHI).
  9. Assist in monitoring and enforcing compliance with data-related policies and regulations such as GDPR, CCPA, and industry-specific standards.
  10. Triage incoming data issues, requests, and inquiries through a ticketing system, ensuring timely and effective resolution.
  11. Collaborate with business users to capture and formalize business rules and data quality rules for critical data elements.
  12. Support the administration and configuration of the data governance platform (e.g., Collibra, Alation, Informatica Axon).
  13. Conduct user acceptance testing (UAT) for new data governance tools, features, and data-related system changes.
  14. Help create and deliver training materials and communications to promote data literacy and awareness of data governance principles across the organization.
  15. Assist in the certification process for critical data elements and reports, validating their fitness for purpose.
  16. Perform regular audits of metadata, reference data, and master data to ensure accuracy and adherence to defined standards.
  17. Support Master Data Management (MDM) initiatives by helping to define matching, merging, and survivorship rules for key data domains like Customer or Product.
  18. Gather and document requirements for new data quality controls and reporting enhancements from various business units.
  19. Analyze and report on the business impact of poor data quality, helping to build the case for data improvement initiatives.
  20. Partner with the data architecture team to review data models and ensure they align with established governance standards and principles.
  21. Facilitate the process for defining and registering new critical data assets within the official data catalog.
  22. Monitor the health and performance of automated data quality rules, escalating failures and performance issues to the appropriate technical teams.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis to answer pressing business questions.
  • Contribute to the organization's broader data strategy and roadmap by providing insights from daily governance activities.
  • Collaborate with business units to translate their functional data needs into technical requirements for engineering teams.
  • Participate in sprint planning, daily stand-ups, and other agile ceremonies within the data and analytics team.
  • Assist in the preparation of presentations and status updates for the Data Governance Council and other leadership forums.

Required Skills & Competencies

Hard Skills (Technical)

  1. SQL Proficiency: Foundational ability to write SQL queries to extract, manipulate, and analyze data from relational databases.
  2. Advanced Excel Skills: Expertise in using advanced functions, pivot tables, and data analysis toolsets within Microsoft Excel.
  3. Data Governance Platforms: Familiarity with the concepts of data governance tools like Collibra, Alation, Informatica Axon, or similar platforms is a major plus.
  4. Data Visualization: Basic experience with BI and data visualization tools such as Power BI, Tableau, or Qlik to create reports and dashboards.
  5. Data Quality Principles: A strong theoretical understanding of data quality dimensions (e.g., accuracy, completeness, timeliness, consistency).
  6. Metadata Management Concepts: Understanding of business, technical, and operational metadata and the role of a data catalog and business glossary.
  7. Data Privacy Awareness: Basic knowledge of key data privacy regulations and concepts (e.g., GDPR, CCPA, PII).
  8. Data Modeling Fundamentals: A foundational understanding of relational and dimensional data modeling concepts.

Soft Skills

  1. Exceptional Attention to Detail: A meticulous and precise approach to work, with a commitment to accuracy and quality.
  2. Analytical & Problem-Solving Mindset: The ability to dissect complex problems, identify root causes, and propose logical solutions.
  3. Superior Communication: Excellent written and verbal communication skills, with the ability to articulate complex data concepts to non-technical audiences.
  4. Collaborative Spirit: A natural team player who can build strong relationships and work effectively with diverse stakeholders across the business and IT.
  5. Proactive & Self-Motivated: A strong sense of ownership and the ability to work independently, manage tasks, and drive initiatives forward with minimal supervision.
  6. Organizational & Time-Management Skills: The capacity to manage multiple priorities, projects, and deadlines in a fast-paced environment.
  7. Inherent Curiosity: A desire to ask "why" and a passion for learning about data, systems, and business processes.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in a relevant field or equivalent practical experience in a data-centric role.

Preferred Education:

  • Bachelor's or Master's degree in a quantitative or technical field.

Relevant Fields of Study:

  • Management Information Systems (MIS)
  • Computer Science
  • Data Analytics or Data Science
  • Business Administration (with a technical focus)
  • Finance or Economics

Experience Requirements

Typical Experience Range:

  • 0-2 years of professional experience, including relevant internships or co-op positions, in a role related to data analysis, business analysis, database management, or IT.

Preferred:

  • Prior internship or full-time experience within a dedicated data governance, data management, or data quality team is highly advantageous.
  • Demonstrable project work (academic or professional) involving data cleansing, data analysis, or process documentation.
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