Develop a profound understanding of Moneyfarm business and functional needs.
Transform raw production grade data into well structured, analytics-ready datasets.
Design, deploy, test and maintain scalable data models in DBT, ensuring quality, performance and auditability.
Translate complex business and regulatory requirements into robust data solutions.
Enable multiple stakeholders (Operations, Compliance, AML, Product, Engineering) to successfully interact with clean, meaningful and purposeful data.
Design, deploy, test and maintain automated reports, dashboards and data tools.
Work closely with both Data Engineering and Data Analytics departments.
Apply software engineering best practices to analytics code (e.g., testing, version control, CI/CD).
Bring positive impact to Moneyfarm data culture by sharing knowledge and promoting best practices.

~2 years of relevant work experience in data analytics or engineering roles
BSc or higher degree in Engineering, Computer Science, Data Science, Statistics or related discipline
Experience in fintech / wealth management
Proficiency in SQL and DBT.
Theoretical and practical knowledge of data modelling principles and best practices.
Experience with Airflow or similar orchestrators, Python.
Experience with BI and reporting tools (Tableau, Metabase, Looker).
Experience with cloud data warehouses (Redshift, Big Query).
Excellent written and verbal communications skills, also with non technical stakeholders.
Ability to work autonomously interacting with multiple stakeholders.
Comfortable working in iterative environments balancing quality and delivery.
Fluency in English is essential (most stakeholders are UK based).

Analytics Engineer – Application Platform

Key skills