At a Glance
- Tasks: Lead a team to modernise and automate commodities data pipelines.
- Company: Bloomberg London, a leader in financial data and analytics.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Join a collaborative team focused on innovation and excellence.
- Why this job: Make a significant impact on data reliability and automation in a dynamic environment.
- Qualifications: Experience in data engineering and team leadership required.
The predicted salary is between 54000 - 66000 £ per year.
Bloomberg London is recruiting for a Team Leader in Data Engineering & Integration for Commodities Data. You will own modernization, stability, and scalability of core commodities data pipelines, overseeing ingestion, transformation, and governance across reference data, fundamentals, curves, and environmental datasets.
You will lead a team to improve automation, monitoring, and controls, while partnering with Data Modelling, Data Quality and regional teams to deliver reliable data for pricing.
Commodities Data Engineering Lead & Automation employer: Bloomberg
Bloomberg is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, you will have access to numerous professional development opportunities while working in a cutting-edge environment that values your contributions to the data manufacturing infrastructure. Located in a vibrant city, Bloomberg provides unique advantages such as a diverse workforce and a commitment to work-life balance, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Commodities Data Engineering Lead & Automation
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Commodities Data Engineering Lead & Automation
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.
