Data Catalog Architect

Designs and implements enterprise data catalog strategies covering metadata management, data discovery, lineage tracking, tagging taxonomies, and platform selection to make organizational data findable and trustworthy.

Platinum

v1.0.10 activationsData & AnalyticsTechnologyexpert

SupaScore

85.7

Research Quality (15%)

8.5

Prompt Engineering (25%)

8.6

Practical Utility (15%)

8.7

Completeness (10%)

8.5

User Satisfaction (20%)

8.5

Decision Usefulness (15%)

8.6

Best for

▸Designing metadata ingestion strategies for DataHub or OpenMetadata implementations
▸Creating enterprise tagging taxonomies with PII classification and domain boundaries
▸Evaluating data catalog platforms (DataHub vs Amundsen vs Collibra) for specific organizational needs
▸Building data lineage tracking across modern data stacks and legacy systems
▸Designing catalog adoption strategies that balance technical architecture with organizational change management

What you'll get

●Detailed metadata model specifications following DAMA DMBOK2 principles with technical, business, operational, and social metadata categories
●Platform comparison matrices evaluating DataHub, Amundsen, and OpenMetadata against specific organizational requirements with implementation complexity scores
●Comprehensive tagging taxonomy hierarchies with governance rules, controlled vocabularies, and lifecycle management policies for classification, domain, quality, and usage tags

Not designed for ↓

×Building custom data catalog software from scratch
×Hands-on data engineering or ETL pipeline development
×Day-to-day catalog administration or user training
×Data quality rule implementation or monitoring setup

Expects

Detailed information about the organization's data landscape including number of sources, existing platforms, user personas, current discovery workflows, and governance maturity level.

Returns

Comprehensive data catalog strategy documents including metadata models, tagging taxonomies, platform recommendations, implementation roadmaps, and adoption frameworks with specific technical configurations.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

data-catalogmetadata-managementdata-discoverydata-lineagedatahubopenmetadatatagging-taxonomydata-governancedata-classificationamundsendata-meshpii-detection

Research Foundation: 8 sources (4 official docs, 4 books)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.12/15/2026

Auto-versioned: masterfile quality gate passed (score: 86.0)

v1.0.02/15/2026

Initial release

Prerequisites

Use these skills first for best results.

Data Warehouse ArchitectGold

Works well with

Data Governance StrategistGold Data Lineage TrackerGold Data Mesh ArchitectGold Data Pipeline ArchitectGold Data Quality EngineerGold

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Data Quality Testing EngineerGold Apache Airflow EngineerGold dbt Analytics EngineerGold

Common Workflows

Enterprise Data Platform Architecture

Complete data platform design starting with warehouse architecture, adding catalog layer for discovery, establishing governance frameworks, and implementing quality controls

Data Warehouse Architect→data-catalog-architect→Data Governance Strategist→Data Quality Engineer

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