Front-Office Data Engineer for Trading Analytics

Mondrian Alpha; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Mondrian Alpha is seeking a robust Data Engineer to join its London front-office technology team, building and maintaining data infrastructure that supports trading, research, and portfolio analytics across a multi-asset platform.

You will own end-to-end data pipelines, ensure access to clean data for portfolio managers, analysts, and technologists, and collaborate with both tech and business stakeholders to improve data quality and platform reliability.

Qualifications

• 5+ years of experience building data pipelines in a financial or trading environment.
• Strong Python and data libraries (pandas).
• Proficient with SQL and relational databases.
• Experience with cloud storage, orchestration and messaging systems.
• Able to handle large, multi-source datasets with a delivery focus.

Responsibilities

• Design, build and optimise scalable data pipelines for analytics and trading.
• Onboard and integrate external and internal data sources.
• Develop and maintain data validation and quality controls.
• Support production data workflows and troubleshoot issues.
• Contribute to data architecture standards and documentation.
• Collaborate with engineering and front-office teams to improve accessibility.
• Occasionally provide out-of-hours support to maintain availability.

Skills

Python

SQL

Data pipelines

Data quality

Stakeholder collaboration

Problem solving

Tools

Cloud storage

Workflow orchestration

Messaging systems

Job description

Mondrian Alpha is seeking a robust Data Engineer to join its London front-office technology team, building and maintaining data infrastructure that supports trading, research, and portfolio analytics across a multi-asset platform.

You will own end-to-end data pipelines, ensure access to clean data for portfolio managers, analysts, and technologists, and collaborate with both tech and business stakeholders to improve data quality and platform reliability.