Data Modeller

L&Q; Greater London; Hybrid; GBP 57,000 - 65,000; Full time

Benefits offered by this job

Pension contribution up to 6%

28 days annual leave rising to 31 with

Westfield Health Cash Plan

Volunteering paid days

Job summary

L&Q is seeking a Data Modeller to join the Data and Information Team. You will shape data landscape across Azure lakehouse, building conceptual, logical, canonical, and dimensional models to deliver trusted insights via Power BI and governed analytics services.

You will work with Data Engineers to translate business requirements into scalable data structures, metadata, and governance controls, supporting data quality and lineage across the platform.

Qualifications

• Experience in advanced dimensional and relational modelling best practices.
• Knowledge of data governance, metadata, lineage and cataloguing.
• Excellent communication and stakeholder management skills.

Responsibilities

• Join a small team of data design professionals to enable data-driven decision making.
• Deliver conceptual, logical, canonical and dimensional models for trusted insights.
• Translate business requirements into data structures, metadata and governance controls.
• Collaborate with Data Engineers to implement models in Delta Lake and lakehouse architecture.

Skills

ERwin Data Modeller

ER/Studio

Sparx Enterprise Architect

Data Modelling

Azure Lakehouse

Power BI

Azure Databricks

Delta Lake

SQL

Stakeholder management

Tools

Erwin Data Modeller

ER/Studio

Sparx Enterprise Architect

Job description

Contract Type: 18-month Fixed-Term Contract, Full-Time, 35 hours

Salary: £57,094 per annum to £65,000 per annum (London weighted salary) or £49,052 per annum to £57,000 per annum (Regional salary), dependant on experience

Grade: 10

Reporting Office: London, Stratford or Manchester, Trafford

Persona: Agile Worker: 20% - 40% of contractual hours to be worked from reporting office/working location (hybrid working)

Closing Date: 22nd October 2026

Interview Dates: 29th-30th October 2026 Please note that in person interviews will be held for at least one of the interview stages for this role.

Benefits include:

Excellent pension plan (up to 6% double contribution), 28 days Annual Leave rising to 31 days with length of service + Bank Holidays, Westfield Health Cash Plan, non-contributory life assurance, up to 21 hours volunteering paid days, lifestyle benefits, Employee Assistance Programme and many more

Early applications are encouraged as we reserve the right to close the advertisement and interview earlier than stated.

L&Q reserves the right to not progress applications for candidates who have had one unsuccessful application/interview process with L&Q for the same or similar role in the previous 12 months.

Join our Data and Information Team at L&Q:

L&Q is one of the UK's largest housing associations and providers of social and affordable homes. We house around 250,000 people primarily across Greater London and Greater Manchester. Our purpose is simple - to provide social homes and landlord services that everyone can be proud of.

• You will have the opportunity to shape the data landscape and transform service delivery.
• The Data Modeller is all about undertaking design to deliver data driven outcomes.
• The role is required to support transformation and change projects.
• The Data Modeller reports to our Data Design Manager, within Data and Information team.

Your impact in the role:

• You will join a small team of fellow data design professionals working collaboratively within the larger Technology department to enable and drive the adoption of data-driven decision-making across the organisation.
• You will have extensive experience of data modelling at all phases from context, through conceptual models to logical and canonical models. You will be a skilled user of an advanced modelling tool such as erwin Data Modeler, ER/Studio or Sparx Enterprise Architect.
• Your primary focus will be on delivering conceptual, logical, canonical and dimensional models that support trusted data products and star schemas for actionable operational, tactical and strategic insights. These models will increasingly be implemented within a modern Azure lakehouse environment and consumed through Power BI and other governed analytics services.
• You will support these models with artefacts such as business glossary and data dictionary entries.
• As L&Q evolves its data platform, the Data Modeller will contribute to the definition and adoption of modelling standards for a medallion lakehouse architecture, working with Data Engineering, Data Governance, Data Quality and Analytics colleagues. The role will help translate platform requirements into practical modelling patterns across Azure Data Factory, Azure Databricks, Delta Lake, Unity Catalog, Microsoft Purview and Power BI, including metadata, lineage, data quality and certification requirements.
• These activities call for individuals who can complement strong relational and dimensional data modelling capabilities with excellent communication and stakeholder management skills, and who can translate business requirements into implementable data structures, metadata, quality rules and governance controls across a modern data platform.
• Working with business to understand the factors influencing delivery performance and efficiency.
• Creating conceptual, logical, canonical and dimensional models and the supporting intellectual property.
• Supporting Information Analysts in exposing actionable insights.
• Supporting Data Assurance Analysts with business rules and metadata.
• Promoting data literacy and utilisation across the organisation.
• Working with industry partner organisations on standards and other collaborative initiatives.
• Defining and applying modelling standards for bronze, silver and gold data layers within a medallion lakehouse architecture.
• Working with Data Engineers to translate logical and dimensional models into implementable Delta Lake structures, including keys, relationships, history, conformed dimensions and data product boundaries.
• Supporting the definition of metadata, lineage, classification, glossary and certification requirements across Unity Catalog, Microsoft Purview and related governance tooling.
• Defining data quality rules, reconciliation requirements and model-level acceptance criteria that can be implemented and monitored within data pipelines.

What you'll bring:

• Extensive experience of tools such as erwin Data Modeller or ER/Studio.
• Knowledge and understanding of advanced dimensional and relational modelling best practices.
• Good understanding of broader data governance and management frameworks and practice.
• Experience in SQL databases and database querying languages preferred.
• Excellent communication skills, both written and verbal.
• Appreciation of the fundamental business value of data and information.
• The ability to present data concepts in business terms.
• Business analysis skills and experience.
• Stakeholder management skills and experience.
• Extensive experience in designing and developing enterprise data models through the process of transitional data architecture delivery.
• Strong practical understanding of modern lakehouse and medallion architecture patterns, including separation of raw, curated and consumption layers.
• Experience modelling data for cloud analytics platforms, ideally Azure Databricks and Delta Lake, or demonstrably equivalent lakehouse technology.
• Working knowledge of Azure data services such as Azure Data Factory, ADLS Gen2 and Power BI, and how data models are implemented and consumed across them.
• Experience defining dimensional models for lakehouse or warehouse implementation, including star schemas, conformed dimensions, surrogate keys and slowly changing dimensions.
• Understanding of metadata-driven governance, data lineage, cataloguing, classification and business glossary practices, with experience of Unity Catalog, Microsoft Purview or equivalent tooling.
• Experience defining data quality rules, reconciliation controls and acceptance criteria alongside logical and dimensional models.
• Good understanding of Delta Lake concepts such as schema enforcement/evolution, versioned data and the implications of append/incremental processing for model design.
• Ability to work effectively with Data Engineering teams using SQL and, ideally, sufficient Python/PySpark literacy to review physical implementation patterns and collaborate on model delivery.
• Understanding of data product, certified data set and governed self-service concepts, including how models support Power BI semantic models and direct SQL consumption.
• Experience contributing to technology evaluation, proof-of-concept activity, architecture/design assurance or migration planning within a data platform transformation.
• Awareness of CI/CD, version control and automated deployment practices for data models, schemas and associated metadata.