Summary: The Data Engineer role focuses on building and supporting data platforms and services for a trading house's Front Office Data & Analytics Engineering team. The position requires hands-on development of scalable data pipelines and cloud-based solutions, ensuring high-quality data for investment decision-making. The engineer will collaborate with Quantitative Researchers and take ownership of solutions throughout their lifecycle. Key technologies include Python, Snowflake, MongoDB, and AWS.
Key Responsibilities:
- Design, develop, and support scalable data pipelines and cloud-based solutions.
- Ensure high-quality, reliable, and timely data is available for investment decision-making.
- Take ownership of solutions from design and implementation to testing, deployment, and production support.
- Collaborate with Quantitative Researchers to translate business requirements into technical solutions.
- Improve data quality through validation and monitoring.
- Support production environments and resolve business-critical data issues.
Key Skills:
- 5+ years' experience in Data Engineering or Software Engineering, ideally in financial services.
- Strong Python development skills and knowledge of software engineering best practices.
- Experience designing, building, and supporting scalable cloud-based data platforms, preferably on AWS.
- Strong experience with Snowflake and NoSQL databases, particularly MongoDB.
- Good understanding of financial markets and investment data.
- Excellent problem-solving, communication, and stakeholder management skills.
Salary (Rate): £800/day
City: London
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Data Engineer – Front Office Data & Analytics A trading house are looking for a Data Engineer to join their Front Office Data & Analytics Engineering team, working alongside Quantitative Researchers and engineering colleagues to build the data platforms and services that support research, trading and portfolio management. This is a hands-on role where you will design, develop and support scalable data pipelines and cloud-based solutions, ensuring high-quality, reliable and timely data is available to power investment decision-making across the business, You will take ownership of solutions throughout their lifecycle, from design and implementation through to testing, deployment and production support. Working with technologies including Python, Snowflake, MongoDB and AWS, you will help evolve our data architecture, improve data quality through validation and monitoring, and contribute to a collaborative, fast-paced engineering environment focused on delivering robust, investment-enabling data solution Required Experience 5+ years' experience in Data Engineering or Software Engineering, ideally within financial services, with strong Python development skills and software engineering best practices (version control, testing and CI/CD). Proven experience designing, building and supporting scalable cloud-based data platforms and pipelines, preferably on AWS, including containerised deployments using Docker. Strong experience working with Snowflake and NoSQL databases, particularly MongoDB, with a solid understanding of data modelling, governance and lifecycle management. Good understanding of financial markets and investment data, with the ability to work closely with Quantitative Researchers and translate business requirements into scalable technical solutions. Demonstrated ownership mindset with excellent problem-solving, communication and stakeholder management skills, including experience supporting production environments and resolving business-critical data issues. This is a £700-800/day contract role based London; on-site.