Lead Data Modeler

Job Purpose:

The Lead Data Modeler role owns enterprise data modelling at RAKBANK, defining and governing the logical and physical models that underpin the Databricks, Unity Catalog, and analytics platforms. It translates business‑defined data standards into canonical models covering core banking, risk, and regulatory entities, ensuring consistent representation across the data landscape. The position is accountable for maintaining semantic consistency, performance, and regulatory compliance across all data platform zones. It governs the business glossary, data dictionary, Unity Catalog taxonomy, and model change processes to ensure clarity and control. The outcome is a single, trusted semantic backbone that reliably supports analytics, AI, and regulatory reporting at scale.

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.