Data Engineer wanted for systematic arm of globally recognised hedge fund to join the growing Data Engineering team where you will support the Commodities business. This opportunity will give you the chance to design, implement and evolve the data platform, including pipeline, repository, data warehouse and data access APIs. You will be working closely with the quant PMs and researchers in a fast-paced environment as you automate and support the Extract, Transform, and Load (ETL) processes from various market data vendors. They are looking for a passionate engineer with strong financial data knowledge, including security master, financial time series (pricing data, etc.) across multiple asset classes, You’ll need to have solid coding skills (Python, Java/C++, SQL), and experience working with large datasets.

If you eat, sleep and breathe data, and have fantastic interpersonal skills, this role is perfect for you!

Requirements 3+ years’ Python experience

Broad knowledge & experience of database concepts with proficiency in SQL and stored procedures

Knowledge of NoSQL databases and big data technologies

Solid experience working with cloud or on-prem technologies and data infrastructure, e.g. workflow management engines, databases, storage & file systems, analytics platforms

Experience processing large and complex datasets

BS in Computer Science, Engineering, Statistics, or related subject Desirable Experience with any of the following: designing and implementing real-time pipelines; data quality and validation; Kafka; Java/C++/Rust/Go

Experience with traditional and/or alternative datasets in the Commodity space Benefits Work directly with all parts of the fund

Market-leading salaries + bonus

Entrepreneurial feel of a small firm with the infrastructure, technology and support that comes with a large company

Inclusive, collaborative work culture Whilst we carefully review all applications, to all jobs, due to the high volume of applications we receive it is not possible to respond to those who have not been successful.