Job Description

Data Governance

Should have data modeling/data architecture experience.

Data Governance Analyst Recap & Key Skills

Core Responsibilities

• Define and manage critical data elements, metadata, classifications, and standards.
• Apply data privacy and regulatory tags (PII, compliance labels, etc.).
• Focus on data classification, validation, and cataloging in data catalogs.
• Develop and validate classification rules to ensure alignment with data protection requirements .
• Work with modern data catalogs such as Collibra, Alation, Informatica (IDMC) .
• Ensure proper definitions and clarity around data usage and ownership.

Governance Role Expectations

• Strong alignment with data protection and privacy requirements .
• Hands-on with Informatica IDMC (preferred, not required).
• No responsibility for access management , but must handle data classification and cataloging.

Candidate Profile

• Hybrid skillset: technical + business acumen .
• Technical skills:
  • SQL, ETL understanding, data profiling, data warehouse knowledge .
  • Ability to read, query, and analyze data .
• Business skills:
  • Work directly with the business, understand data purpose, interpret rules.
  • Recognize and define PII and sensitive data elements .
• Backgrounds that fit best: data modelers or data architects (already familiar with purpose, structure, and proper definitions of data).

Most Important Qualities

• Ability to work with the business is the #1 requirement.
• Direct experience in data governance (rare but highly valued).
• If not experienced, candidates must have the right foundation (data modeling/architecture) so they can be trained.
• Knowledge of compliance is less critical for contractors (often reserved for FTEs).

Top Skills to Highlight :

• Data governance experience (classification, cataloging, metadata, PII identification).
• Strong SQL and data profiling skills.
• Familiarity with data catalogs (Collibra, Alation, Informatica IDMC).
• Business-facing communication and requirements interpretation.
• Background in data modeling or architecture is a strong plus.

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