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About the role
- Analytics Engineer responsible for deploying data models and transforming datasets at Moneyfarm. Collaborating across teams in a fintech environment to enhance data-driven decision-making.
Responsibilities
- 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.
Requirements
- ~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).
Job title
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Not specified
Degree requirement
Tech skills
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