Data Architect / Modeler Databricks

About The Role

The Data Architect / Modeler works closely with business stakeholders, data owners, and application teams to translate business and data requirements into clear, implementable target-state data models and designs on Databricks. This role bridges business understanding and technical execution — ensuring data architecture is consistent, scalable, and aligned with enterprise data strategy.

Key Responsibilities

Define and maintain conceptual, logical, and physical data models aligned with Databricks lakehouse architecture

Translate business requirements, data definitions, and business rules into structured data models and implementable designs

Analyze existing source systems, data structures, relationships, and dependencies to inform target-state architecture

Design data models leveraging Databricks Unity Catalog, Delta Lake, and medallion architecture patterns

Define and apply data architecture standards, patterns, and reusable approaches across delivery programmes

Work closely with engineering teams to ensure data models are technically feasible and implementable on Databricks

Identify and resolve data architecture and modelling gaps across business domains

Support data standardization, metadata management, lineage, and data quality considerations in target designs

Maintain traceability between business requirements and resulting target data structures

Provide hands-on guidance to delivery teams and contribute to continuous improvement of data architecture practices

Required Qualifications

5+ years hands-on experience in data architecture and data modelling

Strong experience translating business requirements into logical and physical data models

Hands-on experience with Databricks platform — Delta Lake, Unity Catalog, medallion architecture patterns

Experience with data architecture standards, patterns, and enterprise data design principles

Proficiency with data modelling tools and notation (ERD, UML, dimensional modelling)

Experience with data governance, metadata management, and data lineage

Strong communication skills with technical and business audiences

Bachelor's degree in Computer Science, Engineering, or related field

Good to Have:

Experience designing and implementing data models on Databricks lakehouse platforms

Expertise with Delta Lake optimization, partitioning strategies, and performance tuning

Experience with Databricks SQL, Spark SQL, and data transformation on Databricks

Complex banking data and financial services data models

Large-scale data transformation or migration programmes on cloud platforms

Experience with dimensional modelling, normalized schema design, or data vault methodology

Familiarity with data quality frameworks and data lineage tools (e.g., OpenMetadata)

Experience with Agile delivery and iterative data architecture design

Master's degree or advanced certifications in data architecture