Full Stack BI Engineer

Staff Full-Stack BI Engineer

Location: Windsor / Hybrid
Team: Data, Analytics & BI
Reports to: BI Manager
Level: Staff

About the role

We're looking for a seasoned BI engineer who thinks in platforms, not just dashboards — someone who brings deep domain expertise in performance marketing or call-centre operations and turns it into data products the business genuinely trusts.

This isn't "Senior but older." It's a different job — focused on design, standards, and cross-domain impact. You'll lead NFS's transition from a SQL Server-centric environment to a modern, scalable platform built on Azure Databricks and Python, while keeping Power BI delivery sharp and stakeholder-ready.

Your domain knowledge is the differentiator. You ask better questions, catch errors faster, and build products users trust — because you understand what the metrics mean and why they matter to the business.

What you'll do

Own complex data products — Take vague, multi-stakeholder asks (like "we need a single view of revenue across all regions") and turn them into governed, trusted BI products from model to report layer.

Architect the platform — Lead the shift to a cloud-native lakehouse on Azure Databricks with Delta Lake and Unity Catalog. Establish Python-first standards and reusable framework patterns for the team.

Rationalise KPIs — Drive "one version of the truth" for core metrics. Work with senior stakeholders to agree definitions and enforce them in the semantic layer.

Govern and secure — Design access controls, RLS frameworks, and documentation standards. Spot risks early — security gaps, interpretability issues, maintainability debt — and resolve them before they compound.

Lead across functions — Partner with Regional Heads and Sales/Ops Directors to shape BI products that align with how the business actually runs. Negotiate the trade-offs that matter.

Raise the team's bar — Define what "good" looks like in modelling, design, and reporting. Mentor Senior and Associate engineers. Build patterns, templates, and libraries others can reuse.

Your toolkit

You'll need deep, hands-on fluency across the modern Azure data stack — and strong bridging skills for the legacy environment you're migrating from.

Python, PySpark, Azure Databricks (Delta Lake, Unity Catalog, pipelines, notebooks, jobs), Azure Data Lake Storage Gen2, Azure Data Factory, Azure Key Vault, Power BI (complex model design, advanced DAX, RLS, performance tuning), SQL / SSMS, Git & CI/CD. Familiarity with Microsoft Fabric is a plus.

Domain expertise

You'll need hands-on experience in at least one of these domains — ideally both. This isn't a nice-to-have; it's what allows you to build data products people actually trust.

Performance Marketing Analytics — Martech infrastructure, lead attribution, campaign optimisation. You're fluent in funnel metrics (impressions, clicks, lead volume, quality indicators) and comfortable with CPL optimisation, A/B testing, creative testing, bid management, and privacy/consent compliance.

Call Centre Operations — Agent performance dashboards, coaching analytics, and conversion funnel analysis from lead to policy. You understand agent-level KPIs, Grade of Service, First-Call Resolution, and how lead quality, experience, product, and time of day drive conversion.

Ideally, you can connect marketing and sales metrics end-to-end — translating lead volume and quality into sales performance expectations and identifying where friction exists in the lead-to-policy journey.

What we're looking for

Significant experience in BI or Data Engineering roles with end-to-end accountability. A track record of designing and owning core data models, semantic layers, and critical business reports. Hands-on production experience with Azure Databricks. Advanced Power BI skills including complex model design, RLS, performance tuning, and measure authoring.

You think platform-first — you build solutions others can reuse, not just point fixes. You raise the bar on documentation, interpretability, and maintainability. You operate well in mid-transition environments where legacy and modern patterns coexist. You use AI tools as leverage for design, code review, and documentation, with critical judgement.

Azure Databricks certifications are a must. A formal degree is beneficial but strong experience and evidence of impact carry equal weight.

NFS is an equal opportunity employer. We welcome applications from all qualified candidates.