At a Glance
- Tasks: Build data pipelines and automate processes using Python, SQL, and Excel/VBA.
- Company: Fast-growing macro hedge fund with a high-performance culture.
- Benefits: Real ownership of projects, autonomy, and exposure to senior decision-makers.
- Other info: Join a dynamic team and enjoy excellent career growth opportunities.
- Why this job: Make a tangible impact on the fund's performance and scalability from day one.
- Qualifications: 1-5 years in a technical role, strong Python and SQL skills required.
The predicted salary is between 36000 - 60000 £ per year.
Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings
A fast-growing macro hedge fund is seeking a technically sharp and curious individual to join a high-impact team at the intersection of technology, data, and investment operations. Operating in a fast‑paced, high‑performance environment, the fund values autonomy, initiative, and smart problem‑solving. This is a unique opportunity to work across all areas of the business – Trading, Risk, Operations, Finance, and Compliance – while helping shape the firm’s technology infrastructure as it scales.
About the Role
From day one you will be given real ownership of projects that span infrastructure, reporting, and tooling, making a tangible impact on the fund’s performance and scalability.
Key Responsibilities
- Build and maintain robust data pipelines and automations using Python, SQL, and Excel/VBA.
- Integrate external data feeds and APIs into internal systems and databases.
- Develop dashboards and reporting tools to support trading, risk, and operations.
- Manage infrastructure hosted on Microsoft Azure, including VMs and storage.
- Use Git for version control and code collaboration.
- Support the onboarding and implementation of AI tools and systems.
- Collaborate with business users to translate requirements into scalable technical solutions.
- Drive automation and efficiency across the firm through hands‑on project ownership.
Ideal Candidate Profile
- 1‑5 years of experience in a technical, data‑focused, or quantitative role.
- Bachelor’s degree in a STEM field (Computer Science, Engineering, Maths, Physics, etc.).
- Strong Python skills for scripting, data processing, and API integration.
- Solid SQL experience for data manipulation and querying.
- Proficiency in Excel/VBA for reporting and automation.
- Familiarity with Microsoft Azure infrastructure and Git version control.
- Excellent problem‑solving and communication skills.
- A proactive, self‑directed mindset and comfort working in a small, dynamic team.
Bonus Points For
- Experience with dashboarding tools (Power BI, Tableau, Streamlit).
- Exposure to Linux scripting or workflow orchestration.
- Understanding of financial markets or investment operations.
Why Apply
- Join a tight‑knit, high‑performing team where your work has direct impact.
- Gain broad exposure across all areas of a growing hedge fund.
- Enjoy real autonomy and ownership from day one.
- Work closely with senior decision‑makers and contribute to meaningful growth initiatives.
If this sounds like a good match – apply today!
Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings in City of London employer: Jobs via eFinancialCareers
At our fast-growing macro hedge fund, we pride ourselves on fostering a dynamic work culture that values autonomy, initiative, and smart problem-solving. As a Data Engineer, you will have the unique opportunity to make a tangible impact from day one, working closely with senior decision-makers across various business areas while enjoying robust employee growth opportunities and a collaborative environment. Join us to be part of a high-performing team where your contributions directly influence the fund's success and scalability.
Contact Details:
Jobs via eFinancialCareers Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings in City of London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jobs via eFinancialCareers!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings at Jobs via eFinancialCareers.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jobs via eFinancialCareers.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings at Jobs via eFinancialCareers, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer (Technology Analyst) | Macro Hedge Fund - Selby Jennings in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Jobs via eFinancialCareers, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jobs via eFinancialCareers. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Jobs via eFinancialCareers
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jobs via eFinancialCareers!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
