At a Glance
- Tasks: Lead market data engineering projects and enhance system performance on AWS.
- Company: Harrington Starr, a dynamic firm in London focused on high-performance analytics.
- Benefits: Competitive salary, mentorship opportunities, and a collaborative work environment.
- Other info: Ideal for those seeking a balance between coding and technical leadership.
- Why this job: Tackle engineering challenges while developing cutting-edge solutions in a supportive team.
- Qualifications: Strong C++ and Python skills, with experience in Linux and data tooling.
The predicted salary is between 70000 - 90000 € per year.
Harrington Starr is seeking a Market Data Engineering Lead to oversee equities data pipelines and infrastructure in London. The role requires strong C++ development experience on Linux and solid Python capabilities for data tooling. The successful candidate will lead project lifecycles, enhance system performance on AWS, and mentor a small team. A collaborative environment with a 50/50 split between coding and technical leadership makes this opportunity ideal for those looking to tackle engineering challenges while developing best-in-class solutions.
C++ Market Data Lead — High-Performance Analytics in London employer: Harrington Starr
Harrington Starr is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to lead projects, mentor a talented team, and enhance your technical skills in a dynamic environment. The company offers competitive benefits and a unique chance to work on high-performance analytics solutions, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land C++ Market Data Lead — High-Performance Analytics in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your C++ and Python projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions related to market data engineering. Practice coding challenges and be ready to discuss your past projects and how they relate to the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace C++ Market Data Lead — High-Performance Analytics in London
Some tips for your application 🫡
Show Off Your C++ Skills:Make sure to highlight your strong C++ development experience in your application. We want to see how you've tackled complex problems and optimised performance in your past projects, especially on Linux.
Demonstrate Your Python Know-How:Since solid Python capabilities are key for this role, don’t forget to mention any data tooling projects you've worked on. We love seeing how you’ve used Python to enhance data processes or improve system efficiency.
Talk About Leadership Experience:As you'll be mentoring a small team, share any previous leadership experiences you have. We’re interested in how you’ve guided others and contributed to project lifecycles, so let us know about your collaborative spirit!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!
How to prepare for a job interview at Harrington Starr
✨Know Your C++ Inside Out
Make sure you brush up on your C++ skills before the interview. Be prepared to discuss your past projects and how you've used C++ in high-performance analytics. Practising coding challenges related to data pipelines can also give you a leg up.
✨Show Off Your Python Skills
Since the role requires solid Python capabilities, be ready to demonstrate your experience with data tooling. Think of specific examples where you've used Python to enhance system performance or streamline processes, especially in a market data context.
✨Understand AWS and System Performance
Familiarise yourself with AWS services relevant to data engineering. Be prepared to discuss how you've optimised system performance in previous roles, particularly in cloud environments. This will show that you can lead project lifecycles effectively.
✨Emphasise Leadership and Collaboration
As this role involves mentoring a small team, be ready to talk about your leadership style and experiences. Share examples of how you've collaborated with others to tackle engineering challenges, as this will highlight your fit for the collaborative environment they’re looking for.
