As an experienced Analytics Engineer at Wrisk, you will be the bridge between raw data and impactful business insights. You will work closely with our Data Engineering team to manage the data pipeline while taking full ownership of the transformation layer, building robust, scalable data models and metrics that serve as the "single source of truth" for the entire organisation and our business partners.
You will own our Business Intelligence and Analytics Stack, and lead the development of insightful reports and dashboards. This includes taking ownership of our external Analytics Products — a key USP of Wrisk. We are looking for a proactive professional who thrives when given a problem statement and the autonomy to deliver a finished solution, from initial data modelling through to the final reporting suite.
What you’ll do
- Data Modelling: Design, develop, and maintain well-documented, tested, and flexible data models within our data warehouse.
- Stack Architecture: Develop and optimise our modern BI and analytics stack, ensuring data is clean, reliable, and performant.
- Metric Definitions: Maintain the logic for our business metrics across our semantic layer, ensuring they are defined consistently across all tools and departments.
- Pipeline Collaboration: Work with Data Engineering to identify and integrate key data sources, maintain accuracy and stability, and align the upstream data structures to support downstream analytics and reporting.
- Software Excellence: Utilise version control (Git), code reviews, and data quality testing to ensure the integrity of our analytics layer.
- Reporting: Design and build high-quality, intuitive dashboards and visualisations that communicate complex data simply and effectively.
- Analytics Products: Take ownership of the maintenance and enhancement of Wrisk’s external-facing analytics products, ensuring they remain a high-performing, reliable product offering for our partners.
- Self-Service Enablement: Build intuitive data marts that empower Analysts and business users to perform their own analysis with confidence.
- Requirements Gathering: Partner directly with stakeholders in Commercial, Operations, Product, and across external partners to deeply understand their reporting needs and translate them into technical specifications.
- Autonomous Problem Solving: Independently identify and implement areas of opportunity in our stack and processes, and troubleshoot data and reporting issues. We expect you to be a self-starter who manages your own roadmap and deliverables.
Requirements
- Experience: 4+ years in Analytics Engineering, Data Engineering, or a technical BI role with architecture experience.
- SQL Expertise: Advanced proficiency in SQL (CTEs, window functions, complex joins, and query optimisation).
- Visualisation Expertise: Significant experience building sophisticated, user-friendly dashboards in modern BI tools (e.g., Looker, QuickSight, Tableau, or Power BI) with a strong eye for data storytelling.
- Modern Data Stack: Hands-on experience with tools like dbt, Snowflake/BigQuery/Redshift, and Fivetran/Airbyte.
- Data Modelling: Strong understanding of data modelling best practice for modern analytics.
- Goal-Oriented: A proven track record of working independently and delivering complex analytics projects from start to finish with minimal supervision.
- Stakeholder Management: Proven ability to collaborate with non-technical business partners and external clients to gather requirements and explain technical trade-offs.
Desirable/advantageous skills and experience:
- Experience working in a fast-paced scale-up environment.
- Knowledge of Python for data manipulation or automation.
- Financial Services or Insurance industry experience.
