Data Engineer

Data Engineer (Junior/Mid-Level), Asset Manager, London (Onsite)

We are working with a specialist asset manager with a long track record of performance that is looking to hire a Data Engineer / Data Scientist to join its lean but growing global technology team.

This role sits at the centre of the firm's evolving data platform, helping to transform investment, operational and reference data into trusted, high-quality data assets that support decision-making across the business. The successful candidate will contribute to the development of cloud-based data infrastructure, analytics and reporting capabilities, working with technologies such as Snowflake, SQL, Python and modern BI platforms while also supporting the firm's growing adoption of AI and machine learning tools within its data and development lifecycle.

The preferred candidate will have a solid grounding in data engineering, analytics or data science, be comfortable working with large and complex datasets, and enjoy collaborating with Investment, Operations, Risk and Technology teams. This is an excellent opportunity for an ambitious data professional looking to broaden their technical skillset across cloud data platforms, business intelligence, AI-enabled development and investment management data.

Responsibilities

• Build and maintain data pipelines, models and datasets within a modern cloud data platform, supporting reporting, analytics and operational processes.
• Develop dashboards and reporting solutions using Sigma, Power BI, Tableau, Looker or similar BI tools for business stakeholders across the firm.
• Support the integration and modelling of investment, operational, market, risk and accounting data while ensuring data quality, validation and documentation standards are maintained.
• Contribute to analytical, data science and AI-related initiatives, including data quality monitoring, automation and AI-enabled development workflows.

Requirements

• 1-4 years' experience in data engineering, data science, analytics or a closely related discipline.
• Good SQL skills with experience using Python and exposure to cloud data warehouse technologies such as Snowflake, Databricks, BigQuery or Redshift.
• Experience building reports, dashboards or analytical solutions using BI platforms such as Sigma, Power BI, Tableau or Looker.
• Strong communication skills, an interest in AI and machine learning technologies, and a desire to work with complex data within a financial services environment.

We can only respond to highly qualified candidates.