At a Glance
- Tasks: Lead the development of cutting-edge data solutions in a global investment bank.
- Company: Join a leading financial technology firm with a strong focus on innovation.
- Benefits: Attractive salary, performance bonuses, and hybrid working model.
- Other info: Exciting opportunities for career advancement in a dynamic environment.
- Why this job: Shape the future of finance with advanced data engineering technologies.
- Qualifications: Proven experience in data engineering and leadership skills.
The predicted salary is between 135000 - 165000 £ per year.
Learn more about the general tasks related to this opportunity below, as well as required skills.
Location: London
Working: Hybrid (3 days/week in office)
Salary: Up to £150k + bonus
The Role
Joining a global investment bank as part of a growing Data Engineering function, working on critical data infrastructure across the business. You will build and enhance modern data solutions using Snowflake, AWS, Python and SQL, working with large-scale financial data.
VP Data Engineer in London employer: MCGREGOR BOYALL ASSOCIATES LIMITED
As a Senior Network Security Engineer at our global financial services firm, you will thrive in a dynamic and inclusive work culture that prioritises innovation and collaboration. We offer competitive benefits, ongoing professional development opportunities, and the chance to work with cutting-edge technologies in a supportive environment that values your expertise and contributions. Join us to be part of a team that is dedicated to delivering secure and resilient network solutions while fostering your career growth.
Contact Details:
MCGREGOR BOYALL ASSOCIATES LIMITED Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land VP Data Engineer in London
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We think you need these skills to ace VP Data Engineer 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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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.
