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- Tasks: Ensure smooth operation of critical data pipelines for high-stakes financial trading.
- Company: Global finance firm based in London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in the finance industry.
- Qualifications: Degree in Computer Science and 3+ years in data engineering or support roles.
- Other info: Collaborative environment with a strong commitment to ethical standards.
The predicted salary is between 43200 - 72000 £ per year.
A global finance firm is seeking to hire a Data Reliability Engineer to join its team in London. The successful candidate will work collaboratively to ensure the smooth operation of critical data pipelines used in high-stakes financial trading.
Candidates should hold a degree in Computer Science along with 3+ years of relevant experience in data engineering or support roles. The role requires proficiency in Windows, Linux, SQL, and Python, with a strong attention to detail and commitment to high ethical standards.
Data Reliability Engineer — Secure, Scalable Finance Pipelines employer: Point72 Careers
Contact Detail:
Point72 Careers Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Reliability Engineer — Secure, Scalable Finance Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and data engineering sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in SQL and Python. This gives us a tangible way to see what you can do beyond the written application.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge. Be ready to discuss how you've tackled data reliability issues in the past—real-world examples go a long way!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Data Reliability Engineer — Secure, Scalable Finance Pipelines
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Windows, Linux, SQL, and Python in your application. We want to see how your skills align with the role of a Data Reliability Engineer, so don’t hold back!
Tailor Your CV: Customise your CV to reflect the job description. Use keywords from the posting to demonstrate that you’re the perfect fit for our team. We love seeing candidates who take the time to make their application stand out!
Be Detail-Oriented: Since attention to detail is key in this role, ensure your application is free from typos and errors. We appreciate candidates who take pride in their work, so double-check everything before hitting send!
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’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Point72 Careers
✨Know Your Tech Inside Out
Make sure you brush up on your skills in Windows, Linux, SQL, and Python. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've ensured data reliability in previous roles. Think about situations where you identified issues in data pipelines and the steps you took to resolve them. This will demonstrate your proactive approach and attention to detail.
✨Understand the Financial Context
Since this role is in a finance firm, it’s crucial to understand the importance of data in high-stakes trading. Familiarise yourself with how data reliability impacts financial decisions and be ready to discuss how you can contribute to maintaining that reliability.
✨Emphasise Ethical Standards
Given the nature of the finance industry, highlight your commitment to ethical standards in data handling. Be prepared to discuss how you ensure compliance and integrity in your work, which is vital for building trust in data-driven environments.
