At a Glance
- Tasks: Develop and maintain KDB+/Q data solutions and analytics for trading.
- Company: UBS, a leading global financial services firm.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on modernising data platforms.
- Why this job: Join a dynamic team to innovate and enhance data-driven trading solutions.
- Qualifications: Experience in data engineering and strong analytical skills required.
The predicted salary is between 63000 - 77000 £ per year.
UBS is seeking a data-focused engineer in London to develop and maintain KDB+/Q based data solutions and analytics. You will build data pipelines, models and reporting datasets, analyze large-scale data, and partner with business stakeholders to deliver effective solutions while driving root-cause analysis and ensuring platform stability.
The role emphasizes collaboration with engineering teams to modernize the broader data platform, handle production applications, and explore AI-driven workflow.
KDB+/Q Data Engineer — Trading Data Pipelines & Analytics in London employer: UBS
UBS is an exceptional employer, offering a dynamic work environment in London where collaboration and innovation thrive. As a CCP Risk Manager, you'll benefit from a culture that prioritises employee growth, providing opportunities to tackle complex challenges while utilising cutting-edge AI technologies. With a commitment to inclusivity and flexible working options, UBS ensures that every team member can contribute meaningfully to our collective success.
StudySmarter Expert Advice🤫
We think this is how you could land KDB+/Q Data Engineer — Trading Data Pipelines & Analytics in London
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We think you need these skills to ace KDB+/Q Data Engineer — Trading Data Pipelines & Analytics in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at UBS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at UBS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at UBS
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
