Lead Enterprise Data Architect

Enterprise Data Architect

We are seeking an experienced and passionate Enterprise Data Architect to build and own foundational enterprise data management capabilities spanning Master Data Management (MDM) Data Governance Data Quality Metadata & Cataloging semantic/context layer engineering and enterprise data architecture. This role combines strategic leadership with handson technical expertise to ensure enterprise data is trusted governed discoverable and ready for analytics AI and operational use.

The Enterprise Data Architect designs governs and evolves the enterprise-wide data architecture that powers analytics AI and operational workflows. You will define standards and reference architectures; guide data modeling and integration patterns; and influence platform decisions across the enterprise data hub/warehouse ecosystem MDM governance and metadata capabilities.

JOB DUTIES

Enterprise Data Architecture Leadership

• Define and maintain the enterprise data architecture strategy reference models and standards
• Create and govern canonical data models domain models and integration patterns
• Ensure architectural alignment across data engineering analytics MDM governance and application teams
• Drive modernization toward cloudnative scalable AIready architectures
• Define architecture guardrails for data security privacy and regulatory compliance in partnership with Security and Legal (e.g. access controls classification retention)

Data Modeling & Canonical Design

• Lead design of conceptual logical and physical data models across domains
• Establish enterprisewide modeling standards naming conventions and modeling patterns
• Partner with MDM and governance teams to ensure consistency across master data reference data and operational data

Semantic / Context Layer Architecture

• Architect and maintain the enterprise context layer (semantic layer) enabling consistent metrics definitions and reusable data entities
• Define metric logic dimensional models and semantic relationships used across BI AI and operational systems
• Ensure alignment with analytics engineering (dbt metric stores semantic tools)

Master Data & Governance Architecture

• Architect MDM solutions including domain models match/merge logic hierarchies and integration patterns
• Partner with governance teams to operationalize policies through technology
• Integrate metadata lineage and governance workflows into the architecture

Data Integration & Platform Architecture

• Define ingestion transformation and consumption patterns across batch streaming and APIbased pipelines
• Architect cloud data platforms (Azure/AWS/GCP) including lakehouse warehouse and realtime components

Metadata Catalog and Lineage Architecture

• Ensure scalability performance security and cost optimization
• Design metadata ingestion patterns and lineage frameworks across pipelines BI tools and MDM systems
• Implement enterprise cataloging solutions using platforms such as Collibra Atlan Alation or similar
• Ensure metadata is complete accurate and actionable for governance and engineering teams

HandsOn Technical Execution

• Build and validate architectural prototypes POCs and reference implementations
• Write SQL design schemas build lineage connectors and define transformation logic
• Troubleshoot complex data architecture issues across pipelines models and platforms

CrossFunctional Leadership

• Partner with data engineering analytics MDM governance product and application teams
• Provide architectural guidance code reviews and technical mentorship

• Communicate architectural decisions to executives engineers and business stakeholders

  YOU MUST HAVE

• 8 years of experience in data architecture data engineering or enterprise architecture
• Deep handson experience with cloud data platforms (Snowflake Databricks Azure AWS or GCP)
• Strong expertise in data modeling (dimensional relational canonical semantic)
• Experience architecting MDM and governance solutions using Collibra Reltio Atlan Informatica or similar
• Strong SQL data pipeline design and metadata/lineage engineering skills
• Experience with modern data stack tools (dbt Spark Kafka Airflow etc.)
• Ability to translate business needs into scalable architectural designs
• Experience with enterprise architecture frameworks (TOGAF DAMADMBOK)
• Background in designing AIready data architectures (feature stores vector stores semantic layers)
• Experience with APIdriven architectures and eventdriven patterns
• Familiarity with data products and data mesh concepts
• Adoption of standardized data models and architectural patterns across the enterprise
• Reduction in data duplication inconsistencies and integration complexity
• Highquality governed discoverable data powering analytics and AI
• Scalable costefficient cloud data platform performance

• Strong alignment between business engineering and governance teams

  WE VALUE

• Experience with enterprise architecture frameworks (TOGAF DAMADMBOK)
• Background in designing AIready data architectures (feature stores vector stores semantic layers)
• Experience with APIdriven architectures and eventdriven patterns
• Familiarity with data products and data mesh concepts

Success Measures

• Adoption of standardized data models and architectural patterns across the enterprise
• Reduction in data duplication inconsistencies and integration complexity
• Highquality governed discoverable data powering analytics and AI
• Scalable costefficient cloud data platform performance
• Strong alignment between business engineering and governance teams

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