Role Overview

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.

Tech Stack

Amazon Redshift
BigQuery
SQL
Tableau

Wrisk

Open Positions (1)

Engineering

Analytics Engineer