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- Tasks: Build the data backbone for advanced investment strategies in a dynamic hedge fund.
- Company: Join a successful hedge fund with a focus on innovation and collaboration.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Work closely with traders and researchers to drive data excellence.
- Why this job: Make a real impact by solving complex data challenges in a fast-paced environment.
- Qualifications: 5+ years in ETL/ELT pipelines, strong knowledge of equities and commodities.
The predicted salary is between 80000 - 100000 £ per year.
An exceptional opportunity to join a successful hedge fund as a Data Engineer where you'll build the data backbone powering advanced investment strategies. This is not a vanilla data role. The team need someone who genuinely understands either equities or commodities (preferably both) products – how each is priced and valued, the market events and behaviours that affect them, and the full operational trade lifecycle. You'll act as the data lead for the asset class build-out, helping to upskill the wider team (from a data perspective rather than analytics) and setting the standard for how this data is sourced, modelled, governed, and consumed. You'll be exposed to the full data flow – ingestion, cleaning, quality assurance, and the build-out of robust data platforms – managing diverse financial datasets spanning market, fundamental, and alternative sources from acquisition through to delivery. Working closely with quant researchers, traders, and engineers, you'll solve complex data challenges and deliver high-quality data to fuel sophisticated trading models in a fast-paced, innovative environment.
Responsibilities
- Develop a deep working understanding of equities and commodities products – pricing, valuation, market behaviour, key events, and the full operational trade lifecycle – and apply that knowledge to data design, modelling, and governance.
- Act as the data lead for the asset class build-out, partnering closely with the newly hired Equities Trader and the incoming Commodities Trader, and helping to upskill the wider team on best practice for handling this data.
- Collaborate with vendors to source and integrate complex datasets, ensuring they meet the firm's exacting standards for trading and research.
- Design and maintain scalable data pipelines that transform raw data into analysis-ready formats, applying top-tier engineering practices for seamless integration with trading systems.
- Build robust validation tooling to ensure data accuracy, timeliness, and integrity in support of quantitative strategies.
- Provide hands-on support for data pipelines, swiftly resolving issues to maintain uninterrupted data flow for trading operations.
Requirements
- 5+ years of experience building ETL/ELT pipelines with Python and pandas in a financial markets trading environment.
- Genuine product knowledge of equities and/or commodities – including how each is priced and valued, the events and market behaviours that drive them, and the operational trade lifecycle.
- Strong expertise in relational databases and SQL.
- Proficiency with technologies such as S3, Kafka, Airflow, or Iceberg.
- Demonstrated experience managing large, complex financial datasets sourced from multiple vendors.
- Confidence working with a team that is newer to these asset classes, bringing the data perspective and lifting the standard around them.
- A passion for engineering excellence and delivering impactful, practical solutions.
- Excellent collaboration and communication skills to thrive in a team environment.
Data Engineer (Hedge Fund) employer: QuanTech Partners
Contact Detail:
QuanTech Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Hedge Fund)
✨Tip Number 1
Network like a pro! Reach out to folks in the hedge fund space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those related to equities and commodities. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of market behaviours and trade lifecycles. Be ready to discuss how you've tackled complex data challenges in the past.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team and contributing to our innovative environment.
We think you need these skills to ace Data Engineer (Hedge Fund)
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let us see your enthusiasm for data engineering! Share specific examples of how you've tackled complex data challenges in the past, especially in financial markets. We love seeing candidates who are genuinely excited about the role and the impact they can make.
Tailor Your Experience: Make sure to highlight your experience with equities and commodities. We want to know how your background aligns with our needs. Use the job description as a guide and weave in relevant projects or roles that showcase your understanding of pricing, valuation, and market behaviours.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Use bullet points where possible to make your skills and experiences stand out. Remember, we’re looking for someone who can communicate effectively!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at QuanTech Partners
✨Know Your Products Inside Out
Make sure you have a solid understanding of equities and commodities. Brush up on how they are priced, valued, and the market behaviours that influence them. This knowledge will not only help you answer questions confidently but also demonstrate your genuine interest in the role.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with ETL/ELT pipelines, especially using Python and pandas. Bring examples of past projects where you've built scalable data pipelines or managed complex datasets. This is your chance to shine, so don’t hold back!
✨Prepare for Collaboration Questions
Since this role involves working closely with traders and quant researchers, think about times when you've successfully collaborated with others. Be ready to share specific examples that highlight your communication skills and ability to upskill team members.
✨Demonstrate Problem-Solving Skills
Expect to face some hypothetical scenarios or case studies during the interview. Practice articulating your thought process for solving complex data challenges. Show how you approach issues methodically and ensure data accuracy and integrity.