Data Modeller (IT)
Data Modeller 6 Month contract initially Based: Hybrid/London - 2 days p/w Rate: £Market rates p/d (via Umbrella company) We have a great opportunity with a world leading organisation where you will be provided with all of the support and development to succeed. A progressive organisation where you can really make a difference. We have a great opportunity for a Data Modeller to join the team. Key Responsibilities:
- Define and maintain conceptual, logical, and physical data models that accurately reflect business processes and support analytics, AI/ML, and operational needs.
- Translate business requirements into robust data entities, attributes, relationships, and constraints; ensure traceability from requirements to models.
- Establish and enforce GDM modelling standards and naming conventions (e.g., normalization, dimensional/star/snowflake patterns, data vault where appropriate).
- Design dimensional models (facts, dimensions, hierarchies, slowly changing dimensions) for BI/analytics and performance at scale.
- Create and manage canonical data models and semantic layers to enable consistent metrics and self service analytics across domains.
- Ensure data quality by design-define integrity rules, reference/master data relationships, and validation checks embedded in pipelines.
- Optimise models for performance and cost (partitioning, clustering, indexing, compression, surrogate keys, distribution strategies).
- Drive data integration design across sources (CDC, event streaming, APIs), mapping source to target, resolving conflicts, and handling historical changes.
- Support AI/ML readiness by modelling features, aggregations, and histories; collaborate on feature stores and model input/output schemas.
- Embed privacy and security requirements into models (PII classification, minimisation, masking, role based access, retention, and residency).
- Proven experience delivering conceptual, logical, and physical data models for cloud data platforms, ideally GCP
- Strong hands on modelling for BigQuery (analytical/columnar patterns, denormalization strategy, partitioning & clustering considerations)
- Expertise in data modelling approaches: 3NF, dimensional (Kimball), Data Vault, and hybrid patterns for Lakehouse designs
- Maintain versioned model artefacts (ERDs, schema scripts, JSON/YAML specs) and change logs; manage controlled evolution of models.
- Ability to translate banking domain requirements (Customer, Accounts, Payments, Credit, Risk, Finance) into scalable canonical models
- Strong understanding of BigQuery performance and cost optimisation impacts driven by modelling choices (query patterns, storage, scan costs)
- Experience designing data products for analytics and reporting with trusted definitions (facts, dimensions, SCD, conformed dimensions)
- Strong knowledge of data governance: metadata management, lineage, stewardship, data quality rules, and critical data elements
- Proficiency with data modelling tools such as ER/Studio, PowerDesigner, ERWin, SQL Developer Data Modeler, or equivalent cloud native tools.
- Familiarity with GCP ecosystem integration (e.g., Cloud Storage, Dataflow/Dataproc, Pub/Sub) and how ingestion patterns influence modelling
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