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- Tasks: Join the Data Engineering team to tackle big data challenges and enhance data quality.
- Company: Be part of one of the world's largest hedge funds with a prestigious tech team.
- Benefits: Enjoy competitive salary, bonuses, personal development allowance, and a vibrant office culture.
- Why this job: Shape technology solutions in a flat, collaborative environment with exciting social events.
- Qualifications: Expertise in Python, large datasets, Linux, and a degree in a relevant field from a top-tier university.
- Other info: Work with cutting-edge tools like Dataiku, Snowflake, and engage in regular team offsites.
The predicted salary is between 43200 - 72000 £ per year.
One of the world’s largest hedge funds, this is an excellent opportunity to join one of the most prestigious technology teams in systematic trading in a wide-ranging development role. With a flat-structured, ‘no-attitude’ working environment, this is a great time to join as engineering is undergoing significant investment.
The Role
Looking for an experienced engineer to join the Data Engineering team. You’ll collaborate with the Data Science team, delivering unique solutions to solve their big data challenges. You’ll also design & implement strategies and tools to monitor & validate data quality for thousands of datasets in use across the firm. Their core systems almost all run on Linux and most code is in Python, including extensive use of numpy, scipy, pandas, scikit-learn, etc. Systems that require the highest data throughput are implemented in Java, and they use Dataiku, Snowflake, Prometheus, and ArcticDB heavily. New tools and libraries are constantly assessed, meaning you can shape the technology landscape and make an impact early on.
Requirements
- Expert programming experience (ideally in Python)
- Understanding of the challenges of dealing with large datasets (structured and unstructured)
- Solid Linux platforms experience with various scripting languages
- Knowledge of modern practices for ETL, data engineering and stream processing
- Degree with high mathematical and computing content – Computer Science, Mathematics, Engineering, Physics, etc. – from a top-tier university
- Working knowledge of at least one database technology, e.g. MongoDB, PostgreSQL, Snowflake, Oracle
Nice to have
- Proficient with a range of open-source frameworks and development tools e.g. NumPy /Pandas, Spark, Apache Kafka
- Previous experience of working with financial market data, especially tick data
- Experience with AWS
Competitive salary + generous bonuses. Extra perks including a personal development allowance and sponsorship. Central London office with a very smart, friendly tech team. Flat-structured, transparent and collaborative environment, ‘no-attitude’ culture. Regular social events, plus annual company trips and team offsites.
Software Engineer – Data employer: Oxford Knight
Contact Detail:
Oxford Knight Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer – Data
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Python, Linux, and data engineering tools like Dataiku and Snowflake. Having hands-on experience or projects that showcase your skills with these technologies can set you apart.
✨Tip Number 2
Network with current or former employees of the company on platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during interviews.
✨Tip Number 3
Prepare to discuss your experience with large datasets and any challenges you've faced in data engineering. Be ready to share specific examples that demonstrate your problem-solving skills and how you’ve successfully implemented solutions in past roles.
✨Tip Number 4
Stay updated on the latest trends in data engineering and big data technologies. Being knowledgeable about emerging tools and practices can show your enthusiasm for the field and your commitment to continuous learning, which is highly valued in a dynamic environment.
We think you need these skills to ace Software Engineer – Data
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your programming experience, especially in Python, and any relevant projects involving large datasets. Emphasise your familiarity with Linux and any database technologies you've worked with.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific tools and frameworks you have experience with, such as NumPy, Pandas, or Snowflake, and how they relate to the job description.
Showcase Relevant Experience: When detailing your work experience, focus on projects that demonstrate your ability to handle big data challenges. Include examples of how you've implemented strategies for data quality monitoring or worked with ETL processes.
Highlight Your Educational Background: Since the role requires a degree with high mathematical and computing content, ensure you mention your qualifications clearly. If you graduated from a top-tier university, make that stand out in your application.
How to prepare for a job interview at Oxford Knight
✨Showcase Your Python Skills
Since the role requires expert programming experience in Python, be prepared to discuss your previous projects and how you've used Python to solve complex problems. Bring examples of your work, especially those involving libraries like NumPy, Pandas, or Scikit-learn.
✨Demonstrate Your Data Handling Expertise
The company is looking for someone who understands the challenges of dealing with large datasets. Be ready to talk about your experience with both structured and unstructured data, and how you've tackled issues related to data quality and validation in past roles.
✨Familiarise Yourself with Their Tech Stack
Research the tools and technologies mentioned in the job description, such as Dataiku, Snowflake, and Prometheus. Showing that you have a working knowledge of these systems will demonstrate your enthusiasm and readiness to contribute from day one.
✨Prepare for Technical Questions
Expect technical questions related to ETL processes, data engineering, and stream processing. Brush up on your knowledge of database technologies like MongoDB or PostgreSQL, and be ready to explain how you've applied these in real-world scenarios.
