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- Tasks: Join a hedge fund as a Data Engineer, managing diverse financial datasets and building data pipelines.
- Company: QuanTech Partners is a leading firm in quantitative finance talent acquisition.
- Benefits: Competitive salary, innovative work environment, and opportunities for professional growth.
- Other info: Mid-senior level role with full-time employment in London.
- Why this job: Be part of a dynamic team solving complex data challenges in the fast-paced financial sector.
- Qualifications: 5+ years in ETL/ELT with Python, strong SQL skills, and experience with large financial datasets.
The predicted salary is between 42000 - 60000 £ 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
Familiarise yourself with the specific technologies mentioned in the job description, such as S3, Kafka, and Airflow. Having hands-on experience or projects that showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the hedge fund and financial services sectors. Attend industry meetups or webinars to connect with potential colleagues or recruiters who might provide insights or referrals for the Data Engineer role.
✨Tip Number 3
Prepare to discuss your experience with ETL/ELT pipelines in detail during interviews. Be ready to share specific examples of challenges you've faced and how you overcame them, particularly in a financial context.
✨Tip Number 4
Showcase your understanding of financial markets and instruments. Being able to speak knowledgeably about how data impacts trading strategies will demonstrate your passion for the role and the industry.
We think you need these skills to ace Data Engineer (Hedge Fund)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ETL/ELT pipelines, Python, and SQL. Emphasise any relevant projects or roles that showcase your ability to manage complex financial datasets.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and the financial sector. Mention specific technologies you’ve worked with, like S3 or Kafka, and how they relate to the role at QuanTech Partners.
Showcase Problem-Solving Skills: Provide examples in your application of how you've solved complex data challenges in previous roles. This could include developing validation tools or maintaining data pipelines under pressure.
Highlight Collaboration Experience: Since the role involves working closely with quant researchers and engineers, mention any past experiences where you collaborated effectively in a team environment to achieve common goals.
How to prepare for a job interview at QuanTech Partners
✨Showcase Your Technical Skills
Be prepared to discuss your experience with ETL/ELT pipelines, particularly using Python and pandas. Highlight specific projects where you successfully managed large datasets and integrated complex data sources.
✨Understand Financial Markets
Demonstrate your knowledge of financial markets and instruments during the interview. This will show that you not only have the technical skills but also understand the context in which you'll be working.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially related to data accuracy and integrity. Be ready to explain how you've tackled similar challenges in past roles.
✨Emphasise Collaboration Skills
Since the role involves working closely with quant researchers and engineers, highlight your collaboration and communication skills. Share examples of successful teamwork and how you contributed to achieving common goals.