Senior Data Analyst
ROLE OVERVIEW
The Data Analytics Engineer enables scale through reusable platform capability rather than bespoke analytics delivery. The role builds and maintains governed data products, analytical models and semantic layers that allow Business Unit Analytics teams to self-serve trusted insight using consistent definitions, reusable patterns and certified data foundations.
KNOWLEDGE AND SKILLS:
Data Product Engineering:
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- Design, build and maintain governed data products on the Group data platform, including bronze, silver and gold layers, reusable data marts and certified analytical data products.
Analytical & Semantic Modelling:
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- Define and maintain semantic models, star schemas, KPI logic and behavioural entities such as events, sessions, journeys, flows, steps, intents and transitions. Maintain definition consistency across channels and business units.
Data Quality, Contracts & Conformance:
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- Implement validation checks, testing frameworks, data contracts, governance controls and certification evidence so that data product quality is demonstrated rather than assumed.
Insight Delivery & Platform Analytics:
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- Build analytical products and Power BI assets that support descriptive, diagnostic, predictive and prescriptive analytics over governed data products.
Enablement & Self-Service:
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- Create reusable datasets, templates, onboarding material, usage guidance and playbooks so that consuming analytics teams can use the data products without re-engineering the foundations.
AI-Enabled & Conversational Analytics:
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- Structure datasets and semantic models so that AI agents, conversational analytics and natural language querying return accurate outputs against governed business logic and definitions.
Automation, Engineering Practice & Operations:
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- Use Python, SQL, Azure DevOps, Git and CI/CD practices to automate analytics delivery, version control solutions and support performance monitoring and optimisation of owned products.
Partnership & Technical Leadership:
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- Partner with analyst product owners, platform engineers, Business Unit Analytics and Business Unit Digital / Technology teams to translate requirements into technically sound, reusable and governed implementations.
Required Experience & Skills:
- 5-10 years of relevant experience as a Data Engineer and Analyst
- Experience in Agile methodologies and ways of work
- Strong experience across data engineering, analytics and data modelling, ideally in digital, channel, behavioural, platform or financial services environments. Experience in enterprise-scale or regulated environments is advantageous.
- Behavioural Analytics technologies experience would be advantageous
MINIMUM EXPERIENCE:
- Bachelors or Masters in Computer Science/ Engineering
- Business Analytics
- Microsoft DP-600 or DP-700 certification preferred.
- DP-203, PL-300, AZ-900 or relevant Databricks certifications recognised.