Love Finance Limited

About Lovey: Lovey is a leading online finance broker and lender dedicated to empowering UK businesses. Since 2016, we have helped thousands of companies access funding through cutting-edge technology. Ranked in the Top 15 fastest growing finance companies, Great Place to Work certified , and holding a 4.9-star Trustpilot rating , we continue to exceed expectations and drive sustainable growth. Role Overview: Analytics Engineer, Lovey Lovey is seeking a commercially minded Analytics Engineer to play a pivotal role in driving business growth. This role sits at the intersection of data, commercial performance, and decision-making, enabling teams to understand what drives revenue clearly, improve conversion, and optimise the end-to-end customer funnel. You will partner closely with sales, marketing, operations, and leadership to ensure commercial decisions are underpinned by accurate, trusted data. By building robust data models, defining core revenue metrics, and delivering actionable insights, you will directly influence how Lovey acquires customers, converts leads, and scales profitably. Role: Analytics Engineer Type: Permanent Location: Hybrid - 2 day per week in Birmingham - minimum Salary: £55,000 to £65,000 per annum Key Responsibilities of Analytics Engineer: Analytics Data Transformation & Modelling Work with existing ELT/ETL data pipelines that ingest data from multiple data sources into a cloud data warehouse (e.g. BigQuery ) Develop and maintain analytics-ready data models and transformations using dbt or Dataform , following analytics engineering best practices Collaborate with data engineering and platform teams to extend and improve datasets within the warehouse Ensure data is accurate, consistent, and trusted across the business Business Intelligence and Data modelling Design and maintain the semantic layer within BI tools (e.g. Looker, ThoughtSpot, or similar) to provide consistent, trusted commercial metrics Model and embed business logic in the BI semantic layer to support revenue, funnels, and lifecycle analysis Build, optimise, and maintain scalable dashboards and structured reports in BI tools, ensuring efficient query performance and accurate metric definitions. Stakeholder Collaboration & Data Enablement Collaborate with product, marketing, sales, and operations teams to understand data requirements and translate them into well-defined models and transformations Work closely with analytics, insights, and data stakeholders to enable accurate, consistent data for reporting and analysis. Support teams by providing reliable, well-documented datasets and semantic models that underpin dashboards and analysis Communicate technical concepts, assumptions, and limitations clearly to non-technical stakeholders Requirements Required Skills & Experience of the Analytics Engineer Strong SQL experience within data warehouses such as BigQuery or equivalent Hands-on experience working with ELT/ETL pipelines Practical experience with dbt, Dataform, or similar transformation frameworks Hands-on experience with at least one BI or analytics tool (Looker, ThoughtSpot, or similar) Proven ability to work with non-technical stakeholders and influence decision-making using data Strong communication skills and a collaborative, commercially focused mindset Nice to Have Experience working with CRM platforms such as Salesforce, HubSpot, or similar Programming experience in Python, JavaScript, or another language to support automation or advanced analytics Experience in a high-growth, fintech, or performance-driven environment Familiarity with experimentation, forecasting, or revenue attribution models