Senior Data Analyst

About the role 
Nucleus Financial Platforms runs its data estate on Microsoft Fabric. The Data team brings together data from across the group's platforms and enterprise systems and turns it into a trusted, well governed foundation for the business. That foundation supports management information, financial reporting, self service analytics, our growing use of AI, and regulatory reporting. 
Data Analysts connect the business, Change and Data Engineering. They make sure requirements are clearly understood and delivered, and that the data the business uses is accurate, consistent and trusted. 
As a Senior Data Analyst you will own larger and less defined pieces of work end to end. You will act as the translation layer between the business, Change and the Data team, completing the up front analysis that data engineering depends on: requirements, source scoping and profiling, data definitions, conceptual and logical models, source to target mappings and non-functional requirements, so that work can be estimated accurately and built without rework. You will also build and release the more complex semantic models and reports yourself, keep the backlog moving, and raise the standard of the analysts around you. 
How we work 
We work in an Agile cycle alongside a Data Product Owner, with work managed through a shared backlog in Azure DevOps. Analysis comes before build: larger items are scoped, profiled, defined and specified before engineering effort is committed, so estimates are accurate and work is built once. Reports and semantic models are version controlled through Fabric Git integration and promoted through Fabric deployment pipelines across development, test and live. Every output is peer reviewed and validated before release, anything touching regulatory reporting carries an additional test and approval gate, and documentation of definitions, mappings and decisions is treated as part of the delivery rather than an afterthought. In this role you will be expected to uphold that way of working and help improve it. 
Responsibilities: 

• Own requirements and specification: Act as the main point of contact between the business, Change and the Data team for your workstream, turning business requirements into build ready technical specifications, and explaining data constraints and options back in plain language.
• Lead analysis for engineering work: Complete the up front analysis for larger items, including source profiling, mapping, model design and non-functional requirements such as refresh frequency, volumes and retention, so that engineering effort can be estimated accurately and built without rework.
• Scope new sources: Establish what data exists in each system in scope, covering structure, volumes, refresh frequency, quality and ownership, how the system exposes its data, whether by API, scheduled file extract or direct database connection, and how it is expected to flow into OneLake and the warehouse.
• Define and model data: Produce conceptual and logical data models, source to target mappings, business definitions and reference data, and get them agreed and signed off with system owners and the business.
• Coordinate systems access: Identify the connections, credentials and API access a new source needs, raise the requests, and work with IT, Information Security and suppliers to get access in place, tested and evidenced.
• Build semantic models and reports: Design, build and release Fabric semantic models, DAX measures, Power BI reports and paginated reports that stand up to scrutiny from senior stakeholders, keeping business logic in the warehouse and measures consistent.
• Manage and burn down the backlog: Triage and size incoming work, agree priority with the Data Product Owner and stakeholders, drive items through to completion, and report throughput and burn down position to the Data Lead.
• Data quality and assurance: Validate outputs and integrated data against source, apply team standards for definitions and reconciliation, log defects, and work with system owners to resolve discrepancies.
• Support engineering through build: Stay close to the data engineers during build and testing, resolve questions quickly, and confirm that what is delivered matches the specification.
• Peer review: Review specifications and outputs from other analysts for correctness, consistency with agreed definitions and downstream impact, using Fabric lineage view and impact analysis to understand what a change affects.
• Business as usual and ad-hoc requests: Absorb day to day data requests alongside planned delivery, triaging effectively to protect delivery time.
• Handle personal and client data responsibly: Know where outputs include personal or client data, apply sensitivity labels and row-level security where appropriate, and work within data protection obligations.
• Mentor analysts: Support analysts and developers through specification review, peer review of outputs and knowledge sharing.
• Document decisions and handover: Maintain documentation of models, definitions, mappings, access arrangements and decisions, so that delivered work can be picked up and supported by anyone in the team.
• Take part in Agile ceremonies: Engaged participation in planning, backlog refinement and retrospectives, and contribute to improving how the team works.

Key Skills: 

• Advanced SQL: Strong SQL for complex analysis, data profiling, query optimisation and reconciliation across systems.
• Requirements to specification: Demonstrated ability to translate business requirements into technical specifications that data engineers can build from without further analysis.
• Data modelling: Experience producing conceptual and logical data models, source to target mappings and reference data definitions, with a solid grounding in dimensional modelling, including star schemas, fact grain and slowly changing dimensions.
• Semantic modelling and DAX: Building semantic models, DAX measures and reports that stand up to scrutiny from senior stakeholders, with a clear view of where logic belongs between the warehouse and the model.
• Systems and integration knowledge: An understanding of how enterprise and corporate systems expose data, for example APIs, scheduled extracts and direct database connections, and what that means for integration design.
• Backlog management and delivery at pace: Experience owning and burning down a backlog, sizing work, prioritising with stakeholders and delivering to committed dates.
• Stakeholder management: Confident working with Change, operations and senior stakeholders, and comfortable challenging scope where it is not deliverable.
• Data quality and governance: Discipline around definitions, lineage and reconciliation, and awareness of data protection obligations where outputs include personal or client data.
• Mentoring: Proven ability to guide analysts and developers and raise standards through review and knowledge sharing.
• Agile working: Experience of working in an Agile delivery environment.

Desirable Experience: 

• Microsoft Fabric: Practical experience of the Fabric Lakehouse, Fabric Data Warehouse, OneLake, Data Pipelines, Notebooks and semantic models, including Direct Lake, Git integration and deployment pipelines. A certification such as DP-600 is welcome but not required.
• Regulated financial services: Experience delivering data used for management, financial or regulatory reporting, and working under formal change control.
• Platform and product domain: Wrap, SIPP, pensions or investment platform data.
• Integration and migration projects: Experience of data analysis on systems integration, migration or platform projects, including working with third party suppliers.
• Python: Working knowledge of Python in Fabric Notebooks for profiling and data handling.

A little about us
We are the Nucleus Group Services Limited and we help make retirement more rewarding. Here at Nucleus, people come first - whether it’s our colleagues, or the advisers and customers we support, we know that working in partnership and collaboration leads to the best outcomes. Together, we’ve shaped the platform to how it is today. We work hard, and we celebrate hard too.
Our ambition is to create a platform with a difference, putting the customer centre stage meant tearing up the rule book and starting from scratch. We’ve come a long way since then, but our mission remains just as focused. That’s why our culture, values, and social responsibility are things we keep at the top of our agenda – because we know they matter and have a big impact.
Our culture is one of the many things that sets us apart from the pack. We want to have an environment where our people feel that they can make a real difference, know they’ll be rewarded for their efforts and more importantly, enjoy themselves at work.
Inclusion and diversity at Nucleus
As with most things in life, who cares, wins. We really care about inclusion.
For us it’s not a tick box exercise; inclusion and diversity are embedded in our culture and everything we do. It’s a commercial imperative. It isn’t about being PC. It’s about being future-relevant and durable. We owe it to ourselves and the industry to ensure we are playing our part in creating a fair, balanced and transparent financial services sector.
More diversity means broader experience, a wider set of perspectives and a better collective ability to problem-solve. And it means being more representative of customer groups, which supports areas such as product development.
At Nucleus, we offer a generous blend of benefits for the things that really matter to our people, including a non-contributory pension, bonus, enhanced parental leave, paid time off for emergencies, health and wellbeing initiatives and flexible working options.