At a Glance
- Tasks: Design reusable data pipelines and collaborate on LLM-enabled workflows.
- Company: Bloomberg, a leader in financial technology with a focus on innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Based in Greater London, offering a collaborative work environment.
- Why this job: Join a dynamic team and shape the future of data infrastructure.
- Qualifications: Proficiency in Python and SQL, with 4 years of data engineering experience.
The predicted salary is between 35000 - 45000 £ per year.
Bloomberg is seeking a Data Engineer to join their Shared Infrastructure team. The role involves designing reusable data pipelines and collaborating on LLM-enabled workflows, contributing to a unified data ecosystem.
Candidates should have proficiency in Python and SQL, along with at least 4 years of experience in data engineering. Ideal applicants will possess a Bachelor's degree in a STEM field and relevant technical expertise, as well as strong communication skills to work effectively across teams.
The position is based in Greater London.
Data Infrastructure Engineer – Shared AI Pipelines in London employer: Bloomberg
Bloomberg is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within the tech community in Greater London. Employees benefit from comprehensive professional development opportunities, competitive compensation, and a commitment to diversity and inclusion, making it a rewarding environment for those looking to advance their careers in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Infrastructure Engineer – Shared AI Pipelines in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Infrastructure Engineer – Shared AI Pipelines 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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Bloomberg, 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 Bloomberg. 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 Bloomberg
✨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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Bloomberg!
✨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.
