Senior Data Engineer

As a Senior Data Engineer you will own the design and delivery of the more complex parts of that platform. You will decide how a new source is onboarded and modelled, what controls it needs before it can be relied on for regulatory and financial reporting, and whether a change is safe to promote. Alongside that you will set the standards the team builds to, lead delivery of significant pieces of work, and develop the engineers around you. It is a hands on engineering role with technical leadership attached, and depending on the shape of the team it may include line management. How we work We work in an Agile cycle alongside a Product Owner. Everything we build is version controlled in Azure DevOps and promoted through Fabric deployment pipelines across development, test and live. Development takes place in an isolated feature workspace, every change is peer reviewed before it reaches production, and anything touching regulatory reporting carries an additional test and approval gate. We cover daily platform health checks, and documentation is treated as part of the build rather than an afterthought. In this role you will be expected to shape that way of working, not simply operate within it. Responsibilities:

• Own platform and pipeline design: Lead the design of ingestion pipelines and warehouse models, from the first review of a source feed through to a live, reconciled and documented pipeline in production.
• Set the engineering standards: Define and evolve the team’s design standards, naming conventions, load patterns and re-runnability requirements, and make sure they are applied consistently across every source.
• Own the cross platform model: Lead the design of the conformed layer of the warehouse, resolving differences in identifiers, hierarchies and status models between source platforms so that group level reporting is consistent and reconcilable back to source.
• Act as technical approver: Provide in depth peer review, give clear and specific feedback, and make the call on whether a change is designed, tested and evidenced well enough to reach production, particularly for regulatory pipelines and semantic models.
• Lead delivery: Work with our Product Owner to scope, break down, estimate and prioritise work, and lead delivery of data and BI projects against business objectives and timelines.
• Strengthen the control environment: Design the validation, reconciliation and monitoring controls that sit around the data, own the judgements they depend on such as materiality thresholds, and provide evidence to risk, compliance and audit reviewers.
• Lead incident resolution and recovery: Take the lead on complex failures, including code and data rollback, establish root cause, and feed the lesson back into standards, documentation and controls.
• Govern the consumption layer: Own semantic model governance, keeping business logic in version controlled warehouse procedures and measures thin, so that a metric means the same thing wherever it is consumed.

• Develop the engineers around you: Mentor colleagues through review, pairing and structured knowledge transfer, and make sure no critical pipeline depends on a single person. Line management: Depending on the structure of the team, line manage one or more engineers, covering objectives, development plans, regular one to ones and performance. *

• Engage senior stakeholders: Work directly with finance, risk, compliance and business leads to turn requirements into deliverable solutions, and be straight with them about what the data can and cannot answer.
• Lead Agile ceremonies: Lead planning, backlog refinement and retrospectives, and drive continuous improvement in how the team works.

• Advanced SQL: Advanced SQL development, optimisation and troubleshooting, including complex stored procedure logic over bi-temporal, large data volumes.
• End to end design ownership: A proven record of designing and delivering pipelines or platforms end to end in a cloud data platform such as Microsoft Fabric, Azure Data Factory, Synapse or Databricks, rather than building only to someone else’s design.
• Deep data warehousing knowledge: In depth understanding of dimensional modelling using the Kimball methodology, conformed dimensions, slowly changing dimensions, surrogate key strategies and incremental load patterns.
• Advanced semantic modelling: Strong semantic model and DAX skills, and a clear view on where logic belongs between the warehouse and the model.
• Python and automation: Confident with Python for parsing, automation and data handling, ideally in a notebook environment.
• CI/CD and change control: Strong working knowledge of branching strategy, pull request policy, environment promotion and secret management, and experience operating change control in a governed environment.
• Data quality by design: Experience designing reconciliation, validation and monitoring controls, and setting the thresholds that decide when a difference is investigated.
• Incident leadership: Calm and methodical during a live data incident, able to lead diagnosis and recovery and to communicate clearly while it is happening.
• Mentoring: A genuine interest in developing other engineers and raising the standard of the team’s output, through review, pairing and day to day support.
• Stakeholder management and delivery: Able to manage priorities, expectations and delivery with senior stakeholders, and to push back constructively where a request is not the right answer.
• Judgement in ambiguity: Comfortable taking an unclear requirement or an undocumented source feed and turning it into a defined, deliverable piece of work.

Desirable Experience:

• Microsoft Fabric: Hands on experience with the Fabric Lakehouse, Fabric Data Warehouse, Data Pipelines, Notebooks, Git integration and deployment pipelines. A certification such as DP-700 is welcome but not required.
• Regulated financial services: Experience delivering data used for regulatory reporting, and working with audit, risk and compliance reviewers.
• Platform and product domain: Wrap, SIPP, pensions or investment platform data.
• Secure file based feeds: Experience with encrypted file transfers, key management and automated decryption within a controlled environment.
• AI and data agents: An understanding of how curated data supports AI use cases, and the governance those outputs require.

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.

Nucleus Financial Platforms runs its data estate on Microsoft Fabric. The Data Engineering team ingests data from the group’s platform systems and enterprise tools, transforms it through a four layer architecture, and delivers it as a curated data warehouse and semantic model layer. That output supports management information, financial reporting, self service analytics, an emerging AI capability, and regulatory returns under FCA and PRA obligations., 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.