At a Glance
- Tasks: Join our Data Team to manage and innovate data pipelines using Python.
- Company: A leading systematic hedge fund focused on delivering data globally.
- Benefits: Enjoy a collaborative culture, opportunities for growth, and a focus on diversity.
- Other info: Experience with big data frameworks and cloud development is a plus.
- Why this job: Make a real impact while working with cutting-edge technology and talented professionals.
- Qualifications: 4+ years in Python, a STEM degree, and SQL proficiency required.
The predicted salary is between 43200 - 72000 £ per year.
Our client, a top systematic hedge fund, are seeking an experienced Python developer to join their Data Team (Alpha Data), which is responsible for delivering vast quantities of data to users worldwide. This role involves becoming a technical subject matter expert and developing strong relationships with quant researchers, traders, and colleagues across the Technology organisation. The Data teams deploy valuable data quickly, ensuring ingestion pipelines and data transformation jobs are resilient and maintainable, with data models designed in collaboration with researchers for efficient query construction and alpha generation. The team builds frameworks, libraries, and services to enhance quality of life, throughput, and code quality. They value teamwork, collaboration, excellence, diversity of thought, and creative solutions, emphasizing a culture of learning, development, and growth.
Responsibilities:
- Manage Data Pipelines: Take part ownership of the expanding estate of data pipelines, ensuring they are robust, efficient, and scalable.
- Innovate and Improve: Propose and contribute to new abstractions and improvements, leveraging your Python expertise to make a significant positive impact across the team globally.
- Technical Development: Design, implement, test, optimize, and troubleshoot data pipelines, frameworks, and services, utilizing your knowledge of SQL and RDBMS systems like Postgres.
- Collaborate with Researchers: Work closely with researchers to onboard new datasets, ensuring seamless integration and efficient data flow.
- Lead Production Support: Regularly take the lead on production support operations during normal working hours, applying your practical knowledge of data transfer protocols and tools such as FTP, SFTP, HTTP APIs, and AWS S3.
Required Skillset:
- 4+ years of experience coding to a high standard in Python.
- Bachelor's degree in a STEM subject.
- Proficiency in SQL and familiarity with one or more common RDBMS systems (primarily Postgres).
- Practical knowledge of commonly used protocols and tools for data transfer (e.g., FTP, SFTP, HTTP APIs, AWS S3).
- Excellent communication skills.
- Experience with big data frameworks, databases, distributed systems, or Cloud development.
- Nice to have - Experience with any of these: C++, kdb+/q, Rust.
If you feel the above is a good match to your experience, apply today!
StudySmarter Expert Advice🤫
We think this is how you could land Python Developer (Data Pipelines) | Top Systematic Hedge Fund
✨Tip Number 1
Familiarise yourself with the specific data pipeline technologies mentioned in the job description, such as AWS S3 and various data transfer protocols. Being able to discuss these tools confidently during your interview will demonstrate your technical expertise and readiness for the role.
✨Tip Number 2
Showcase your collaborative skills by preparing examples of how you've worked with cross-functional teams in the past. Since this role involves close collaboration with researchers and traders, highlighting your teamwork experience can set you apart from other candidates.
✨Tip Number 3
Stay updated on the latest trends in data engineering and Python development. Mentioning recent advancements or best practices during your discussions can illustrate your commitment to continuous learning and innovation, which aligns with the company's culture.
✨Tip Number 4
Prepare to discuss your problem-solving approach, especially in relation to optimising data pipelines. Be ready to share specific challenges you've faced and how you overcame them, as this will highlight your practical knowledge and ability to contribute positively to the team.
We think you need these skills to ace Python Developer (Data Pipelines) | Top Systematic Hedge Fund
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your Python development experience, especially in relation to data pipelines. Include specific projects or roles where you've managed data ingestion and transformation.
Craft a Compelling Cover Letter:In your cover letter, emphasise your experience with SQL and RDBMS systems like Postgres. Mention any relevant projects that showcase your ability to innovate and improve data processes.
Showcase Collaboration Skills:Since the role involves working closely with researchers and other teams, provide examples of past collaborations. Highlight how you’ve successfully integrated new datasets or improved data flow in previous positions.
Highlight Technical Expertise:Detail your technical skills, particularly in Python and any big data frameworks you've worked with. If you have experience with data transfer protocols like FTP or AWS S3, make sure to include that as well.
How to prepare for a job interview at Career Wallet
✨Showcase Your Python Expertise
Be prepared to discuss your experience with Python in detail. Highlight specific projects where you've developed data pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Collaboration Skills
Since the role involves working closely with researchers and other teams, share examples of how you've successfully collaborated in the past. Emphasise your ability to communicate complex technical concepts to non-technical stakeholders.
✨Prepare for Technical Questions
Expect questions related to SQL, RDBMS systems like Postgres, and data transfer protocols. Brush up on these topics and be ready to solve problems or write code during the interview to demonstrate your technical skills.
✨Emphasise Continuous Learning
The company values a culture of learning and development. Share how you stay updated with industry trends, any courses you've taken, or personal projects that showcase your commitment to growth in the field of data engineering.
