Montpellier Resourcing
Data Analytics Engineer
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💸£ Competitive plus EXCELLENT bonus and benefits
đź“ŤBased in London (Hybrid)
Due to exciting growth, a fantastic opportunity has arisen to join an established provider of regulatory and compliance intelligence to the financial services sector, as they seek a Data Analytics Engineer to lead the build of its first centralised data warehouse and analytics function. The business supports banks, asset managers, and other regulated firms in interpreting and acting on complex regulation, and is now investing in the data infrastructure to match. This is a ground-up build: there is no existing data team or warehouse to inherit, giving genuine ownership of how the architecture is shaped, alongside the early-stage reality of source mapping, stakeholder alignment, and iterative delivery before the build takes shape. The role sits within Finance and works closely with Revenue Operations and Operations teams.
Key Responsibilities of the Analytics Engineer:
- Data Warehouse Delivery: Lead the design and build of a cloud data warehouse (e.g. Snowflake or BigQuery), from source mapping through to governed, business-ready data.
- Source System Integration: Audit and reconcile data from core systems including CRM, finance/ERP, and platform usage sources into a single, coherent data model.
- Pipelines & Governance: Define ETL/ELT pipelines and establish data governance standards - ownership, data dictionaries, quality checks, and access controls appropriate to a regulated environment.
- Semantic Layer: Build and maintain a reporting layer (e.g. dbt) that ensures consistent metric definitions across the business, such as revenue, retention, and engagement metrics.
- BI Platform Ownership: Lead the selection and implementation of a BI platform (Power BI preferred), taking it from setup through to embedded, business-wide adoption.
- Dashboard Delivery: Design and build core reporting covering pipeline, renewals, product usage, and financial performance, agreed jointly with business stakeholders.
- AI-Enabled Reporting: Establish best practice for using AI tools to support the build and maintenance of dashboards, while ensuring figures remain accurate and auditable.
- Data Arbitration: Act as the trusted source when figures from different systems conflict, resolving discrepancies and embedding the agreed logic into the reporting layer.
- Stakeholder Enablement: Train Finance, Operations, and Revenue teams to self-serve from the BI environment, and translate technical constraints into plain language for non-technical stakeholders.
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Requirements of the Analytics Engineer:
- 3-6 years' experience as a Data Analyst, Analytics Engineer, or similar, ideally within a B2B SaaS environment.
- Proven experience scoping and delivering a data warehouse or lakehouse project from scratch, not just working within one already built.
- Strong, independent SQL - comfortable with complex joins, window functions, and CTEs.
- Hands-on experience with at least one modern data stack tool: Snowflake, dbt, Fivetran, Airflow, or equivalent.
- Working knowledge of CRM data structures, ideally Salesforce, including where data quality typically breaks down.
- Experience implementing and administering a BI platform (Power BI, Tableau, or Looker), including data modelling within the tool and driving user adoption.
- Practical experience applying AI tools within reporting or analytics workflows.
- Strong communication skills, with the ability to explain technical constraints clearly to non-technical stakeholders.
- Comfortable operating with ambiguity and incomplete data, and confident producing a useful answer without waiting for perfect inputs.
- Desirable: exposure to subscription/recurring revenue metrics, financial data, regulated or compliance-driven data environments, and Python or R.
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This vacancy is being advertised by Montpellier Resourcing Associates Limited. The services advertised by Montpellier Resourcing Associates Limited are those of an Employment Agency.
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