At a Glance
- Tasks: Lead projects and mentor junior engineers in a dynamic Data Engineering team.
- Company: Award-winning systematic hedge fund known for its collaborative and friendly culture.
- Benefits: Flexible work schedule with only 3 days onsite, plus competitive salary and career growth.
- Other info: Opportunity to work closely with quantitative developers and enhance your financial tech expertise.
- Why this job: Join a tech-modernising firm and work on exciting greenfield projects with cutting-edge technologies.
- Qualifications: 5+ years in software/data engineering with strong Python and SQL skills.
The predicted salary is between 70000 - 90000 £ per year.
Senior Data Software Engineer with expertise in Python, SQL, databases, Linux, and Docker sought by one of the early Systematic Hedge Funds – an award-winning firm renowned for their collaborative and friendly culture.
You will join a six-person Data Engineering team as one of the more senior engineers, owning projects and helping lead and mentor junior team members. The team has a broad remit across ingestion, storage, transformation, and distribution of tick, timeseries, reference, and alternative datasets. The business is currently midway through massive technology modernisation, therefore there is ample opportunity to work on greenfield projects and with new technologies.
We are looking for someone passionate about technology who stays current with industry trends, follows engineering best practices, and is always looking for opportunities to improve systems, processes, and performance.
- Developing ELT / ETL pipelines to ingest and transform datasets with Python, Snowflake, and dbt.
- Building a streaming platform (Kafka, Flink, Iceberg) to capture and aggregate large volumes of tick data.
- Working closely with quantitative developers, researchers, and portfolio managers.
- Supporting Java-based live data feed handlers.
Requirements:
- 5+ years working as a Software Engineer and/or Data Engineer.
- Strong expertise in Python, SQL, and a good understanding of relational databases.
- Confident working with Linux and Docker. AWS experience preferred.
- Skills in Java and/or Kafka, Flink, and Iceberg preferred.
- Cloud Data Warehousing experience preferred, especially using Snowflake.
- Financial experience – especially in relation to Buy Side, Electronic Trading, and Market Data.
This is an excellent long-term opportunity for a talented Data Software Engineer to take on a more senior role in a specialist Systematic Hedge Fund renowned for their friendly working culture and work/life balance (i.e. only 3-days per week onsite).
Senior Data Software Engineer - Systematic Hedge Fund (London) in City of London employer: Winston Fox
Join an award-winning systematic hedge fund in London, where a collaborative and friendly culture fosters innovation and growth. As a Senior Data Software Engineer, you will have the opportunity to lead projects, mentor junior team members, and work on exciting greenfield initiatives within a modernised tech environment. With a strong emphasis on work/life balance and flexible onsite requirements, this role offers a meaningful career path in a supportive setting that values your expertise and passion for technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Software Engineer - Systematic Hedge Fund (London) in City of London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Senior Data Software Engineer - Systematic Hedge Fund (London) 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 Winston Fox, 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 Winston Fox. 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 Winston Fox
✨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 Winston Fox!
✨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.
