All fields marked * are required
• Develop and maintain conceptual and logical models per subject area with clear entity definitions, relationships, grain statements, and business keys — workshopped and signed off with QBE SMEs.
• Design physical models optimised for Databricks/Delta Lake: gold-layer dimensional models (star schemas, conformed dimensions, SCD strategy), silver-layer integrated structures, partitioning/clustering choices, and naming standards.
• Define surrogate/business key strategy, historisation (SCD1/2, effective dating, bitemporal where required), late-arriving data handling, and reference/master data structures with the MDM/governance teams.
• Translate models into build-ready artefacts — DDL, model diagrams, mapping inputs for BDAs — and review engineering implementation for model fidelity.
• Run the model change-control process: versioning, impact analysis for source or requirement changes, and a decision log for modelling trade-offs.
• Align models with QBE enterprise/reference architecture and industry insurance model patterns; rationalise legacy warehouse structures during migration.
• Partner with BI/reporting teams so semantic layers (Power BI) map cleanly onto gold structures; guide aggregate/summary design for actuarial and finance consumers.
• Act as onshore modelling counterpart for the offshore squad: unblock modelling questions daily and represent modelling decisions in client design forums.
• 10+ years in data roles with 6+ years dedicated modelling across conceptual/logical/physical layers on warehouse and lakehouse platforms.
• Expert dimensional modelling (Kimball) — conformed dimensions, fact types, SCDs, bridge/hierarchy patterns — plus 3NF/integration-layer modelling; Data Vault 2.0 awareness.
• Hands-on modelling for Databricks/Delta Lake or comparable cloud platforms — understands how modelling choices play out in Spark (joins, partitioning, file sizes, merge behaviour).
• Insurance domain modelling — P&C strongly preferred: policy/coverage/risk hierarchies, claims and transaction facts, premium earning patterns, reinsurance structures, party/role models.
• Professional modelling tooling: erwin, ER/Studio, SqlDBM, or PowerDesigner, with disciplined metadata and versioning.
• Strong SQL; able to prototype and validate models against real data volumes.
• Experience working as client-facing onshore anchor with an offshore build team.
• Unity Catalog metadata alignment; Purview/Collibra glossary integration.
• Exposure to ACORD or vendor insurance data models; actuarial data marts (triangles, reserving data).
• Graph or semantic modelling; dbt model governance.
• CDMP or equivalent data-management certification.
• Bachelor’s/Master’s in Computer Science, Information Systems, Mathematics, or related discipline.
• Explains modelling trade-offs in business language; earns SME trust quickly.
• Meticulous documentation habits — the model is the contract.
• Collaborative but decisive when consensus stalls; keeps a written decision log.
Required
Preferred
All fields marked * are required
• Develop and maintain conceptual and logical models per subject area with clear entity definitions, relationships, grain statements, and business keys — workshopped and signed off with QBE SMEs.
• Design physical models optimised for Databricks/Delta Lake: gold-layer dimensional models (star schemas, conformed dimensions, SCD strategy), silver-layer integrated structures, partitioning/clustering choices, and naming standards.
• Define surrogate/business key strategy, historisation (SCD1/2, effective dating, bitemporal where required), late-arriving data handling, and reference/master data structures with the MDM/governance teams.
• Translate models into build-ready artefacts — DDL, model diagrams, mapping inputs for BDAs — and review engineering implementation for model fidelity.
• Run the model change-control process: versioning, impact analysis for source or requirement changes, and a decision log for modelling trade-offs.
• Align models with QBE enterprise/reference architecture and industry insurance model patterns; rationalise legacy warehouse structures during migration.
• Partner with BI/reporting teams so semantic layers (Power BI) map cleanly onto gold structures; guide aggregate/summary design for actuarial and finance consumers.
• Act as onshore modelling counterpart for the offshore squad: unblock modelling questions daily and represent modelling decisions in client design forums.
• 10+ years in data roles with 6+ years dedicated modelling across conceptual/logical/physical layers on warehouse and lakehouse platforms.
• Expert dimensional modelling (Kimball) — conformed dimensions, fact types, SCDs, bridge/hierarchy patterns — plus 3NF/integration-layer modelling; Data Vault 2.0 awareness.
• Hands-on modelling for Databricks/Delta Lake or comparable cloud platforms — understands how modelling choices play out in Spark (joins, partitioning, file sizes, merge behaviour).
• Insurance domain modelling — P&C strongly preferred: policy/coverage/risk hierarchies, claims and transaction facts, premium earning patterns, reinsurance structures, party/role models.
• Professional modelling tooling: erwin, ER/Studio, SqlDBM, or PowerDesigner, with disciplined metadata and versioning.
• Strong SQL; able to prototype and validate models against real data volumes.
• Experience working as client-facing onshore anchor with an offshore build team.
• Unity Catalog metadata alignment; Purview/Collibra glossary integration.
• Exposure to ACORD or vendor insurance data models; actuarial data marts (triangles, reserving data).
• Graph or semantic modelling; dbt model governance.
• CDMP or equivalent data-management certification.
• Bachelor’s/Master’s in Computer Science, Information Systems, Mathematics, or related discipline.
• Explains modelling trade-offs in business language; earns SME trust quickly.
• Meticulous documentation habits — the model is the contract.
• Collaborative but decisive when consensus stalls; keeps a written decision log.
Required
Preferred