Senior Data Modeller

TN United Kingdom; City of Edinburgh; Hybrid; GBP 50,000 - 90,000; Full time

Job description

Location: Edinburgh or Glasgow or Alderley Edge

Working style: Hybrid 50% home/office based

Royal London is seeking a Senior Data Modeller to join the Core Data Engineering function. This role is key to the development of the Royal London Enterprise Data Platform (EDP), a data lakehouse built using Azure Databricks.

The platform supports digital use cases, effective decision-making through feature-engineered data products, self-service analytics and downstream data feeds.

This role will be part of a small team responsible for the ongoing maintenance, optimization and extension of the data models which will drive the EDP design and development.

About the Role

• Maintaining data models at conceptual, logical and physical level.
• Understanding and clarifying business requirements and working with Business Analysts and Data Engineers to design and implement changes to data structures.
• Working as part of the Data Modelling team to help establish and improve our modelling processes and standards.
• Data Mapping: Documenting the mapping and transformation logic to get source system data into our conformed layer and from there into denormalised structures in the curated layer as required.
• Strategic Alignment: Ensures data modelling aligns with the Enterprise Data strategy, Business strategy, and Technology strategy.
• Coherence and Flexibility: Maintains a coherent data model that aligns with the operating model, change budgets, and Total Cost of Ownership (TCO), while being extensible and flexible for future opportunities.
• Collaboration: Works closely with the Principal Data Engineer and Data Architects to ensure alignment with the end-to-end data domain architecture, integrating with existing architecture design authorities and boards.
• Advocacy: Collaborates with Product Owners to promote the EDP as a tool to democratise data and enhance return on insight within Royal London.

About You

• Data Modelling Expertise: Possesses excellent skills in data modelling and enterprise-wide data architecture, with strong knowledge of all levels of data modelling and complex source-to-target mappings for various interfaces (batch, near real-time, streaming/event-based).
• Proven Experience: Demonstrates a proven track record in data modelling for complex projects, with strong experience in data warehousing concepts (Kimball, Inmon, star schemas, OLAP, data lakes).
• Technical Proficiency: Skilled in using data modelling tools (preferably Idera ER/Studio Data Architect) and knowledgeable about cloud data and analytics services on Microsoft Azure (e.g., Azure Data Factory, Databricks). Proficient in ETL concepts, including data cleansing, change data capture (CDC), integration, mapping, extraction, transformation, and loading.
• Communication and Collaboration: Excellent at communicating and documenting technical information, with extensive experience in agile practices and implementation. Works closely with third-party authorities and suppliers/partners and has a good understanding of regulations and legislation within the financial services market.

About Royal London

We’re the UK’s largest mutual life, pensions, and investment company, offering protection, long-term savings and asset management products and services.

Our People Promise to our colleagues is that we will all work somewhere inclusive, responsible, enjoyable and fulfilling. This is underpinned by our Spirit of Royal London values; Empowered, Trustworthy, Collaborate, Achieve.

We've always been proud to reward employees by offering great workplace benefits such as 28 days annual leave in addition to bank holidays, an up to 14% employer matching pension scheme and private medical insurance.

Inclusion, Diversity and Belonging

We’re an Inclusive employer. We celebrate and value different backgrounds and cultures across Royal London. Our diverse people and perspectives give us a range of skills which are recognised and respected – whatever their background.