Lead Data Modeler

Lead Data Modeler

What You Will Do

• Design and maintain enterprise logical data models across core banking domains, aligned to business standards and EA architecture patterns.
• Own physical data model design in Databricks Delta Lake, including schemas, partitioning, Z-ordering, and storage optimisation across all platform zones.
• Govern Unity Catalog taxonomy, ensuring complete asset registration, ownership, classification, and metadata accuracy.
• Collaborate with Lead Data Engineering to translate logical models into physical implementations and validate pipeline outputs.
• Own the enterprise business glossary and data dictionary in Collibra or equivalent, ensuring steward-approved, version-controlled definitions.
• Support domain-oriented data products aligned to Data Mesh principles, ensuring discoverability and self-description.
• Design dimensional and analytical schemas optimised for Databricks SQL and Power BI consumption.
• Define modelling specifications for AI and ML feature stores aligned to canonical enterprise models.
• Ensure compliance with CBUAE data classification, privacy standards, and internal governance policies.
• Govern data model change management, assessing downstream impact and maintaining a versioned model catalogue.

What You Will Bring

• 8+ years in data modelling and architecture, including 3+ years in a lead role within regulated financial services.
• Expert proficiency in logical and physical data modelling on Databricks Delta Lake and Unity Catalog.
• Strong knowledge of dimensional modelling, Data Vault 2.0, and domain-centric data product design.
• Hands-on experience with data governance platforms such as Collibra or Alation.
• Deep understanding of banking data domains, ISO 20022, GL structures, and CBUAE regulatory reporting.
• Proven collaboration with Data Architects, Data Engineers, and Analysts.
• Bachelor’s degree in a relevant field; CDMP or Databricks certification preferred.

Desired

• Advanced Databricks / Delta Lake modelling at enterprise scale.
• Unity Catalog governance and metadata management experience.
• Ownership of business glossary, data dictionary, and semantic layer.
• Applied dimensional and Data Vault modelling for analytics and regulatory reporting.
• Experience operating in regulated banking environments.
• What We are not Looking for:
• ❌ A
• reporting‑only or documentation‑centric profile
• that produces diagrams and dictionaries but does not take end‑to‑end ownership of canonical models and their enforcement across the data platform.
• ❌ A
• pure data engineer or DBA
• focused primarily on pipelines, performance tuning, or infrastructure, without deep accountability for enterprise logical modelling and semantic consistency.
• ❌ A modeler
• without banking and regulatory depth
• , who cannot confidently model core banking, payments, GL, and CBUAE regulatory constructs in a governed environment.
• ❌ A hands‑off role‑player
• unable to influence and partner
• with Data Architects, Data Engineers, Business Data Stewards, and Analytics teams to drive adoption of canonical models.
• ❌ A candidate
• uncomfortable with governance and accountability
• , or who views business glossary ownership, data stewardship alignment, and model change control as secondary or optional.