At a Glance
- Tasks: Be the go-to person for traders and researchers on data reliability and quality.
- Company: Join a leading trading firm in London with a cutting-edge environment.
- Benefits: Competitive salary, dynamic work culture, and opportunities for growth.
- Other info: Work with innovative technologies and enjoy a collaborative team atmosphere.
- Why this job: Make a real impact in a fast-paced trading environment while honing your technical skills.
- Qualifications: 3+ years in Data Engineering or related roles, strong Python skills required.
The predicted salary is between 48000 - 72000 £ per year.
One of our clients in the Trading & Market Making space is looking for an engineer to serve as a frontline point of contact for traders, researchers and internal users of data platforms within the London based trading team. This role sits in the nexus between Data Engineering and Reliability & Operations Engineering, and is an excellent opportunity to work in a dynamic, impactful function within one of the most cutting edge trading environments in the city!
What You'll Do:
- Serve as frontline POC for traders, internal users and research teams for everything relating to data reliability.
- Investigate and resolve data quality concerns and freshness anomalies.
- Monitor ingestion pipelines, processes and real time feeds.
- Triaging and addressing alerts promptly to minimize impact on trading.
- Manage relationships with external vendors and resolve upstream issues, specification changes and ensure accurate delivery of datasets.
- Document and relay clear updates to users during production events.
Technical responsibilities:
- Ingest, configure and operationalise new datasets.
- Develop and maintain ETL/ELT data pipelines to feed real time trading and research systems.
- Implement data quality checks, anomaly detection and monitoring frameworks.
- Build and maintain high performance API's to expose market and reference data to trading, research and analytics platforms.
Who you are:
- 3+ years in Data Engineering, SRE, SWE or Data Ops roles in high performance, time sensitive environments.
- Strong Python proficiency, including exposure to libraries such as Pandas, Arrow, and Spark.
- Strong grasp of data modelling, normalization and API development for large scale analytical or trading systems.
- Experience with lakehouse architectures (Databricks ideally, or Delta Lake).
- Exposure to real time and historical market data within Fixed Income, ETFs or Equities would be excellent.
- Operational instincts - extreme agency and ownership over issues, tackling issues with initiative.
Data Operations Engineer employer: Radley James
Radley James is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the tech industry. With a focus on collaboration and employee growth, team members are encouraged to take ownership of their projects while working with cutting-edge technologies in a hybrid London setting. The company values creativity and offers unique opportunities for professional development, making it an ideal place for passionate individuals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Operations Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the trading and data engineering space on LinkedIn. A friendly message can go a long way, and you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to data pipelines or API development, make sure to highlight that in conversations. It’s a great way to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for those technical interviews! Brush up on your Python skills and be ready to discuss your experience with data quality checks and ETL processes. Practising common interview questions can really help you stand out.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, we love seeing familiar names pop up!
We think you need these skills to ace Data Operations Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Operations Engineer role. Highlight your experience in data engineering and any relevant projects you've worked on that showcase your skills in Python, ETL processes, and data quality checks.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data operations and how your background makes you a perfect fit for our dynamic trading environment. Don’t forget to mention your operational instincts and ownership over issues!
Showcase Relevant Experience:When filling out your application, be sure to showcase your experience with lakehouse architectures and any exposure to real-time market data. This will help us see how you can hit the ground running in our fast-paced environment.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!
How to prepare for a job interview at Radley James
✨Know Your Data Inside Out
Make sure you brush up on your data engineering concepts, especially around ETL/ELT processes and data quality checks. Be ready to discuss your experience with Python libraries like Pandas and Spark, as well as any relevant projects you've worked on that involved real-time data.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled data quality concerns or resolved issues in high-pressure environments. Think about times when you had to triage alerts or manage relationships with external vendors, and be ready to explain your thought process.
✨Understand the Trading Environment
Familiarise yourself with the trading and market making space, particularly around Fixed Income, ETFs, and Equities. Being able to speak the language of traders and researchers will show that you’re not just technically proficient but also understand the business context.
✨Communicate Clearly and Effectively
During the interview, practice relaying complex information in a clear and concise manner. You might be asked to explain how you would document and update users during production events, so think about how you can convey technical details without overwhelming your audience.
