Data and AI Modeler
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Key skills for this role
About the Role
MultiBank Group seeks a Data and AI Modeler to design and govern data models for AI systems and BI dashboards. Responsibilities include dimensional modeling, semantic layer design, feature store architecture, and data quality frameworks.
Key Skills for This Role
Responsibilities
- Design and implement enterprise data models including star schema, snowflake schema, Data Vault 2.0, and wide denormalised models
- Own the data model for core business domains (users, transactions, products, events, financial data)
- Collaborate with data engineers to ensure physical implementation performs efficiently on Databricks, Snowflake, or BigQuery
- Design and maintain the semantic layer using dbt Metrics, LookML, or similar
- Enforce metric governance with single, documented, auditable definitions
- Design and build data foundation for ML feature engineering, producing clean, reliable, point in time correct feature datasets
- Architect and implement feature store integration using Feast, AWS SageMaker Feature Store, or custom solutions
- Implement data quality frameworks using dbt tests and Great Expectations
- Build and maintain data lineage documentation
- Work closely with data analysts, BI engineers, and AI engineers to understand data needs
Requirements
- 4 to 9 years of experience in data modeling, data warehousing, or data architecture
- Deep expertise in dimensional modeling, Data Vault 2.0, and modern lakehouse architectures
- Advanced SQL and dbt skills
- Experience designing semantic layers or metrics layers for BI consumption
- Understanding of ML feature engineering and data requirements of machine learning systems
- Familiarity with data governance, data cataloguing, and metadata management practices
- Strong communication skills
Full Job Posting
Role Overview
- We are looking for a Data and AI Modeler to own the design, implementation, and governance of our data models.
- Ensure every AI system, BI dashboard, and analytical workload is built on clean, well structured, semantically consistent data.
- This is a specialist role at the intersection of data architecture and AI enablement.
Key Responsibilities
- Design and implement enterprise data models including star schema, snowflake schema, Data Vault 2.0, and wide denormalised models.
- Own the data model for core business domains including users, transactions, products, events, and financial data.
- Collaborate with data engineers to ensure physical implementation performs efficiently on Databricks, Snowflake, or BigQuery.
- Design and maintain the semantic layer using dbt Metrics, LookML, or similar.
- Enforce metric governance: every key business metric has a single, documented, auditable definition.
- Design and build the data foundation for ML feature engineering.
- Architect and implement feature store integration using Feast, AWS SageMaker Feature Store, or custom solutions.
- Implement data quality frameworks using dbt tests and Great Expectations.
- Build and maintain data lineage documentation.
- Own the data catalogue for modelled data layers.
- Work closely with data analysts, BI engineers, and AI engineers to understand their data needs.
- Provide training and documentation for self serve access to well modelled data.
Role Requirements
- 4 to 9 years of experience in data modelling, data warehousing, or data architecture roles.
- Deep expertise in dimensional modelling, Data Vault 2.0, and modern lakehouse architectures.
- Advanced SQL and dbt skills. You write production grade transformation code.
- Experience designing semantic layers or metrics layers for BI consumption.
- Understanding of ML feature engineering and the data requirements of machine learning systems.
- Familiarity with data governance, data cataloguing, and metadata management practices.
- Strong communication skills. You explain data model design decisions clearly to both technical and business audiences.
Why Join Us?
- Work with one of the world’s leading financial derivatives institutions.
- Competitive salary plus performance based incentives.
- Access to a dynamic, international, and fast growing environment.
- Strong opportunities for career progression within a global financial group.
- Be part of a business committed to innovation, excellence, and long term growth.
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