Job Description

Python Data Engineer
3-6 Months initial contract
London/Hybrid - 1-2 days per week on site
Negotiable rate (Inside IR35)

We are seeking an experienced Python Data Engineer to join a high-performing data engineering team, building and enhancing centralised data services used by quantitative researchers, traders and front-office teams.

The ideal candidate will have experience in Hedge funds, Asset management or Investment banks

As well as a good understanding of Quant engineering/Quant data groups, Fixed income, rates, FX, macro, trading or pricing environments

This is a hands-on engineering role focused on designing, developing and maintaining scalable data platforms, pipelines and services that deliver high-quality, validated investment data. You'll work closely with technical stakeholders to improve data quality, build reusable data capabilities and support business-critical analytics.

Key Responsibilities
Design, develop and enhance Python-based data services used by front-office and quantitative teams.
Build scalable data pipelines and services to ingest, transform and deliver high-quality datasets.
Develop robust data validation frameworks to improve the accuracy and reliability of derived data.
Work closely with quantitative researchers, traders and engineering teams to understand data requirements and expected outputs.
Cleanse, filter and validate raw datasets to ensure data quality before they are consumed by downstream users and applications.
Support the centralisation of data services, reducing duplication and improving consistency across multiple data sources.
Contribute to the design and implementation of scalable, reusable data architecture rather than tactical point solutions.
Build and maintain APIs and data platforms capable of serving large-scale financial datasets.
Take ownership of solutions throughout the full software development lifecycle, from design and development through testing, deployment and production support.
Promote engineering best practices, including automated testing, version control and CI/CD.
Deploy and maintain applications within cloud-native and containerised environments.
Collaborate with cross-functional teams to continuously improve data platforms supporting pricing, risk, analytics and investment processes.

Required Skills & Experience
Strong commercial Python software engineering experience.
Experience building scalable data services, APIs, data pipelines or data platforms.
Solid software engineering practices including automated testing, Git and CI/CD.
Experience working with cloud platforms, ideally AWS.
Experience with Docker or other containerisation technologies.
Knowledge of Snowflake and NoSQL databases such as MongoDB.
Experience working with large-scale datasets and data transformation processes.
Strong stakeholder engagement skills with the ability to work alongside technical users and engineering teams.

Desirable Experience
Experience within financial services.
Exposure to front-office, quantitative research, trading, market data, pricing, risk or investment data environments.
Experience developing high-performance data solutions in fast-paced organisations.

This is an excellent opportunity to join a technically strong team delivering modern data engineering solutions within a challenging and rewarding environment.

Disclaimer:

This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change.