At a Glance
- Tasks: Join our Global Oil desk to develop data infrastructure and support trading strategies.
- Company: Engelhart, a dynamic commodities trading company with a collaborative culture.
- Benefits: Competitive salary, bonus plan, 25 days holiday, and robust benefits package.
- Other info: Inclusive environment promoting diversity and excellent career development opportunities.
- Why this job: Gain hands-on experience in trading and quantitative research with mentorship from industry experts.
- Qualifications: Recent degree in Computer Science or related field; experience with data-heavy projects.
The predicted salary is between 60000 - 80000 £ per year.
About Us
Engelhart was founded in 2013 by BTG Pactual Group as a commodities trading company. Our business model is “asset light” and highly diversified – giving us the ability to adapt effectively and nimbly to changing market conditions. We have assembled successful multidisciplinary teams, leveraging advanced fundamental analysis with deep quantitative and weather research capabilities. Our activities are underpinned by strong risk management practices and by powerful technology and operational excellence. We have exceptional teams with diverse global backgrounds and decades of experience, and are driven by a highly collaborative culture, across products and competencies. In 2024, Engelhart acquired Trailstone, a global energy trading and technology company. The acquisition provides us with new expertise, analytics and proprietary technology which is being used to provide risk management and optimisation services to help maximise the value of our clients’ renewable power. The acquisition also expanded Engelhart’s capabilities into physical natural gas across North America, a critical fuel to support the energy transition. Our talented and experienced individuals work together according to its four company values: Performance, Agility, Collaboration, Entrepreneurship.
About the Role
We have a new opportunity for a technically strong Quantitative Developer to join our growing Global Oil desk in the London office. This role sits at the intersection of data engineering, quantitative research and trading, with direct exposure to PnL-driven decision-making. We will provide direct and hands-on mentorship from senior quants and portfolio managers, offering the opportunity to gain insights into hedge fund data strategy and macro trading. The successful candidate will play a key role in building and optimising data infrastructure that supports investment decisions, while developing a strong commercial understanding of financial markets at desk. This will be a full-time role, owning the following responsibilities:
- Assisting with the design and implementation of scalable architectures for large time-series datasets (market, economic and alternative data).
- Developing and maintaining data pipelines to ingest, clean, and store structured and unstructured datasets.
- Improving and optimising data querying, storage formats and indexing to enable efficient analysis.
- Managing and enhancing database environments, ensuring high performance and reliability.
- Working closely with portfolio managers and traders to ensure data is actionable and aligned with commercial needs.
- Identifying opportunities to extract commercial value from data, not just collecting it.
- Contributing to data standards, documentation and automation of workflows.
- Supporting the development of tools and datasets that directly impact trading strategies and PnL.
About You
This person will gain direct exposure to real-world trading and macro strategy, collaborating closely with experienced quants and traders. As a result, we believe the following background of experiences and skills will best set up this person for success:
- A recent degree in Computer Science, Data Science, Engineering or a related quantitative discipline.
- Experience working on market modelling, quantitative research or data-heavy projects (academic or professional).
- An understanding of time-series data structures, databases and processing techniques.
- Prior exposure to a bank, trading house, hedge fund or physical trading environment is advantageous.
- Any trading experience or strong market interest is highly valued.
In addition, the following technical skill set will be complimentary:
- Experience with SQL and Python.
- An understanding of libraries such as pandas, NumPy or similar.
- Familiarity with time series databases (e.g., kdb+, InfluxDB, TimescaleDB) is a plus.
- Knowledge of cloud-based data solutions (AWS, Azure, GCP) is preferred.
What we offer
Competitive compensation and participation in Engelhart’s discretionary bonus plan. 25 days of annual holiday entitlement, excluding UK public holidays. Robust benefits package such as medical, dental, life insurance, generous pension contribution, and supplemental benefits partially subsidised by the Company. Eligibility to receive external and internal training in accordance with our Training & Development Policy. We believe in inclusivity and are therefore dedicated to ensuring all employees – across gender identity, race, ethnicity, sexual orientation, religion, life experience, background and more – feel welcome and included in the company. We promote diversity because we believe it is essential to our ability to think holistically.
Quantitative Developer in London employer: Engelhart
Engelhart is an exceptional employer that fosters a collaborative and inclusive work culture, providing employees with direct mentorship from seasoned professionals in the dynamic field of quantitative development. Located in London, the company offers competitive compensation, a robust benefits package, and ample opportunities for professional growth through training and development initiatives, making it an ideal place for those seeking meaningful and rewarding careers in the energy trading sector.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Engelhart on LinkedIn. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio of projects that highlight your experience with data engineering and quantitative research. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your SQL and Python skills, and be ready to tackle some technical questions or coding challenges during the interview process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Quantitative Developer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Quantitative Developer role. Highlight any relevant projects or coursework that showcase your data engineering and quantitative research capabilities.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about this role and how your background fits with our company values. Be sure to mention any specific experiences that demonstrate your agility and collaborative spirit.
Showcase Your Technical Skills:Don’t forget to include your technical proficiencies, especially in SQL and Python. If you’ve worked with time-series databases or cloud solutions, make sure to highlight that experience as it’s super relevant for us.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Engelhart
✨Know Your Tech Inside Out
Make sure you’re well-versed in SQL and Python, as these are crucial for the role. Brush up on libraries like pandas and NumPy, and be ready to discuss how you've used them in past projects.
✨Understand the Market Landscape
Familiarise yourself with current trends in commodities trading and macro strategies. Being able to discuss recent market movements or data-driven insights will show your genuine interest and understanding of the field.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges in previous roles or projects. Highlight your experience with time-series data and how you’ve optimised data pipelines or querying processes.
✨Emphasise Collaboration
Engelhart values teamwork, so be ready to share experiences where you’ve worked closely with others, especially in a quantitative or trading environment. Discuss how you can contribute to a collaborative culture and support portfolio managers and traders.