Data Analytics Engineer

About Pockit + Monese Pockit and Monese are the all-in-one money apps that make it easy for people to access and manage the financial tools that put them in control of their money. We provide vital financial services, from e-money accounts through to income advance products to over three million customers across the UK and Europe. In October 2024, Pockit acquired Monese, creating the leading fintech for anyone who is budgeting, saving, or just trying to stay on top of their finances. Both firms are regulated by the FCA. Following the acquisition of Monese, the business is on a trajectory of growth as the two organisations harmonise and integrate in both the UK and across Europe. The Role As a Data Analytics Engineer, you will drive the transformation layer of our data platform. Working closely with BI, Data Engineering and Data Science, you will design and run our data models, transitioning raw ingested data into high-performance, analytics-ready assets. This role is perfect for a technical specialist who enjoys the "engineering" side of analytics, applying best practices to data transformation and ensuring our Snowflake+AWS native infrastructure is scalable, cost-effective, and reliable. What you will be doing Build and maintain the end-to-end transformation logic from Raw to Business-Ready (Gold) tables on our Snowflake DataWarehouse. Develop and monitor complex data workflows using dbt (running on Airflow), ensuring consistency, high availability and timely data delivery. Partner with the BI team to ensure data models are optimized for Tableau performance and ease of use. Play a key role in the rearchitecture efforts on our data platform as we move towards a Lakehouse on AWS (Iceberg, Glue, Athena) while getting the most out of Snowflake; ensuring efficient compute usage and storage. What we are looking for You have expert-level SQL skills with a good understanding of dimensional modeling (Kimball) and Data Vault 2.0 principles. Significant experience building production-grade models in dbt and managing DAGs within Airflow. Hands-on experience with Snowflake, including understanding of virtual warehouses, clustering, and RBAC security. Experience preparing and optimizing data sources for Tableau. Experience working with Apache Iceberg (or similar formats like Delta/Hudi) to manage large-scale datasets. What we consider a plus Legacy System Migration: Experience extracting data from Azure SQL Server or workflows running on Azure Data Factory is a big plus. So is familiarity with Power BI. Experience auditing and reducing Snowflake credit consumption. What benefits we offer Hybrid working. Enhanced sick days, day off on birthday, voluntary day, days off for a wedding and more. Working abroad flexibility. Learning and development support scheme. Ample opportunity for personal growth at one of the leading Fintech startups in Europe. Flat structure with open communication where everyone has a voice High degree of autonomy in a motivated and talented international team Monese+ Pockit premium account