Data Engineer

Undisclosed; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Undisclosed in London is seeking a Mid/Senior Data Engineer to join a lean global tech team focused on an investment data transformation programme. You will design scalable data solutions, migrate complex data from legacy systems, and work with both business and tech stakeholders to deliver data-driven outcomes.

The role emphasises data quality, performance, and reliable reporting across critical financial datasets, with a strong chance to influence AI strategies in the investment domain.

Qualifications

• 4+ years in data engineering across the data lifecycle.
• Strong SQL and Python skills with BI tools (Sigma/Power BI).
• Experience with Snowflake and ETL processes on financial data.

Responsibilities

• Design and build scalable data solutions for operations, analytics and AI initiatives.
• Migrate investment data from legacy platforms to a modern enterprise architecture.
• Collaborate with stakeholders to translate requirements into data products.
• Ensure data quality, performance and reliability of critical datasets and reporting.

Skills

SQL

Python

Sigma

Power BI

Investment data

Tools

Snowflake

ETL

Job description

Mid/Senior-Level Data Engineer, 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 to join its lean but growing global tech team. In this role, the hire would be central to a major investment data transformation programme, transforming and modernising the firm’s investment systems, data, and reporting capabilities while helping shape the firm’s future data and AI strategy.

The preferred candidate will have strong technical foundations, enjoy working with complex datasets and be comfortable working with a broad range of technical and non-technical stakeholders. This is a great opportunity for a proactive, entrepreneurial data specialist who likes to tackle complex, high-value data challenges and enjoys working at the heart of the investment business.

Responsibilities

• Design and build scalable data solutions to support investment operations, reporting, analytics, and AI initiatives.
• Migrate and integrate complex investment data from legacy vendor platforms into a modern enterprise data architecture.
• Work closely with business and technology stakeholders to understand requirements and deliver effective data-driven solutions.
• Ensure data quality, performance, and operational reliability across critical financial datasets and reporting processes.

Requirements

• 4+ years’ experience in data engineering working across the entire data lifecycle.
• Proficiency in SQL, Python, Sigma / Power BI (or other business intelligence platforms); experience with Snowflake and data ETL processes.
• Experience working with complex financial datasets and a solid understanding of investment, accounting, performance, or risk data.
• Strong communication and stakeholder management skills, able to work effectively with both technical and non-technical audiences.