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- Tasks: Lead data quality and automation strategy for commodities data, ensuring robust controls.
- Company: Bloomberg, a leader in data-driven solutions with a diverse and inclusive culture.
- Benefits: Competitive salary, inclusive workplace, and opportunities for professional growth.
- Why this job: Make a real impact in a dynamic environment while working with cutting-edge data technologies.
- Qualifications: 4+ years in data management, strong SQL and Python skills, and experience in commodities preferred.
- Other info: Join a collaborative team focused on innovation and career development.
The predicted salary is between 48000 - 72000 £ per year.
Location: London
Business Area: Data
Description & Requirements describes the role and responsibilities in the context of Bloomberg's data-driven environment.
The Senior Data Management Professional role will own the data quality and automation strategy across our commodities data landscape, embedding robust controls and tooling across the full commodities data lifecycle. The role combines strategic direction setting with hands-on technical leadership, working closely with a distributed team of data professionals and engineering teams to deliver scalable, automated solutions.
You’ll need to have:
- 4+ years experience in data management, data operations, or data controls, with a strong track record in data quality ownership; commodities, energy, or trading environments strongly preferred.
- Demonstrable experience leading and/or mentoring a data team, setting clear priorities, and managing stakeholder expectations at senior levels.
- Solid technical grounding: advanced SQL; extensive experience with Python or similar for implementing data checks and imputation logic; familiarity with modern data platforms and data quality/observability tooling.
We’d love to see:
- Solid understanding of commodities data (market data, curves, fundamentals) and common platforms (cloud, data management systems, workflow tools).
- Experience defining data quality and automation strategy and operating models in a complex, regulated environment.
- Good understanding of DataOps principles and how to embed them into data engineering workflows to improve reliability and speed of delivery.
- Comfortable operating as a bridge between data ops, engineering, and the business, able to move between high-level strategy and hands-on detail when needed.
- Experience designing and implementing AI/ML solutions, with a well-defined validation framework.
Does this sound like you? Apply if you think we’re a good match. We’ll get in touch to let you know what the next steps are!
If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law. Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email amer_recruit@bloomberg.net.
Senior Data Management Professional - Data Quality, Commodities Data employer: Bloomberg L.P.
Contact Detail:
Bloomberg L.P. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Management Professional - Data Quality, Commodities Data
✨Tip Number 1
Network like a pro! Reach out to your connections in the data management field, especially those who work with commodities. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a case study that highlights your experience with data quality and automation strategies. This will give you an edge during interviews and show that you mean business.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing common questions related to data management and your technical skills. The more comfortable you are, the better you'll perform when it counts.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data Management Professional - Data Quality, Commodities Data
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Management Professional role. Highlight your data quality ownership and any relevant experience in commodities or trading environments to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led data teams or implemented data quality strategies, and don’t forget to show your passion for data management!
Show Off Your Technical Skills: We love seeing technical prowess! Be sure to mention your experience with SQL, Python, and any data quality tools you’ve used. If you’ve worked on AI/ML solutions, give us the details – we want to know how you can contribute!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Bloomberg L.P.
✨Know Your Data Inside Out
Make sure you have a solid understanding of commodities data, including market data, curves, and fundamentals. Brush up on your knowledge of common platforms and data management systems, as this will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL and Python in detail. Think of specific examples where you've implemented data checks or automation strategies. This is your chance to demonstrate your technical grounding and how it aligns with the role's requirements.
✨Demonstrate Leadership Experience
Highlight any experience you have in leading or mentoring a data team. Be ready to talk about how you've set priorities and managed stakeholder expectations. This will help convey your ability to operate at both strategic and hands-on levels.
✨Bridge the Gap Between Teams
Prepare to discuss how you've successfully collaborated between data ops, engineering, and business teams. Share examples of how you've moved between high-level strategy and detailed execution, showcasing your versatility and communication skills.