At a Glance
- Tasks: Design and build scalable data pipelines for critical Economics datasets.
- Company: Bloomberg, a leader in data-driven technology solutions.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and mentorship.
- Why this job: Join a dynamic team to modernise data workflows and make a real impact.
- Qualifications: Bachelor's degree in relevant field and 4+ years of data engineering experience.
The predicted salary is between 60000 - 80000 € per year.
Location: London
Business Area: Data
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Description & Requirements
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem‑solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team:
The Economics Data team is responsible for onboarding, modelling, maintaining, and improving Economics datasets that are fit for purpose for our clients. Our data supports workflows across the Bloomberg Terminal, BQL, Enterprise, and other Bloomberg products. We manage macroeconomic, government, survey, forecast, time‑series, and vendor‑supplied datasets. Our focus is to deliver Economics data that is accurate, timely, scalable, well‑structured, and ready to use.
What’s the Role:
The Economics Data team is looking for a Senior Data Management Professional – Data Engineering to help modernise our data platform and build scalable, resilient data workflows for critical Economics datasets. This role is focused on designing, building, and improving data pipelines, workflow orchestration, automation, monitoring, and technical infrastructure. You will reduce technical debt, modernise legacy processes, and embed quality controls directly into data pipelines and systems. You will work closely with Data, Engineering, Product, and Domain experts to deliver reliable data solutions that improve speed, scalability, observability, and maintainability across the Economics data lifecycle.
We’ll trust you to:
- Build, maintain, and optimise scalable data pipelines for critical Economics datasets.
- Modernise legacy workflows, reduce technical debt, and improve performance, reliability, and maintainability.
- Design automated pipeline controls for validation, monitoring, schema change, exception handling, and data integrity.
- Develop workflow orchestration, alerting, observability, and remediation processes.
- Translate business and client needs into engineering‑ready requirements and scalable technical solutions.
- Partner with Engineering on platform evolution, architecture, tooling, system design, and reliability.
- Apply automation, AI, machine learning, or statistical techniques to improve ingestion, enrichment, validation, and monitoring.
- Own data migrations, workflow redesigns, and technical transformation initiatives.
- Establish best practices for pipeline design, code quality, testing, documentation, version control, and operational handover.
- Influence data modelling, metadata, lineage, and lifecycle management practices from a technical implementation perspective.
- Mentor team members and raise the bar for technical execution, design thinking, and engineering discipline.
You’ll need to have:
- A bachelor’s degree or above in Computer Science, Engineering, Statistics, Mathematics, Economics, Quantitative Finance, or equivalent experience.
- 4+ years of experience designing and building scalable data solutions, ETL pipelines, data workflows, and monitoring frameworks.
- Strong hands‑on experience with Python or similar programming/scripting languages.
- Experience with querying structured, semi‑structured, and unstructured datasets.
- Experience with workflow orchestration, observability, monitoring, alerting, and scalable architecture design.
- Ability to analyse, refactor, and modernise legacy systems.
- Strong understanding of data lifecycle management, data integration, data modelling, data profiling, and data governance.
- Experience building automated controls and reliability frameworks into data pipelines.
- Strong communication skills with the ability to collaborate across Data, Engineering, Product, Vendors, and other stakeholders.
We’d love to see:
- Experience with Economics, macroeconomic, government, survey, forecast, time‑series, or vendor‑supplied datasets.
- Bloomberg Terminal, BQL, Enterprise, or Bloomberg data workflow experience.
- Experience productionising AI, machine learning, anomaly detection, NLP, classification, or LLM‑assisted workflows.
- Experience with cloud platforms, CI/CD, automated testing, version control, metadata management, lineage, or modern DataOps practices.
- Project management experience with Agile delivery, backlog management, JIRA, or similar tools.
- CDMP certification, or progress towards it, is a plus.
If this sounds like you: We encourage you to apply. If you feel you are a strong fit, please submit your application through our career portal. Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, colour, gender identity or expression, genetic predisposition or carrier status, marital status, nationality 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.
Senior Data Management Professional - Data Engineer - Economics Data in London employer: Bloomberg L.P.
Bloomberg is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. As a Senior Data Management Professional, you will have access to cutting-edge technology and the opportunity to work alongside industry experts, enhancing your skills while contributing to impactful data solutions. With a strong commitment to employee growth and diversity, Bloomberg provides a supportive environment where your contributions are valued and recognised.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Management Professional - Data Engineer - Economics Data in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their products, and be ready to discuss how your skills can help them modernise their data platform. Practice common interview questions and have your own questions ready.
✨Tip Number 3
Show off your projects! If you've worked on relevant data engineering projects, make sure to highlight them during interviews. Bring examples of your work that demonstrate your ability to build scalable data solutions and improve workflows.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team. Don’t hesitate – get your application in today!
We think you need these skills to ace Senior Data Management Professional - Data Engineer - Economics Data in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Senior Data Management Professional. Highlight your experience with data pipelines, automation, and any relevant projects that showcase your skills in data engineering.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data management and how your background aligns with our needs. Don’t forget to mention any specific experiences with Economics datasets!
Showcase Your Technical Skills:We want to see your technical prowess! Be sure to include your hands-on experience with Python, ETL processes, and any cloud platforms you've worked with. This is your moment to impress us with your technical know-how.
Apply Through Our Website:We encourage you to apply through our career portal. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Bloomberg L.P.
✨Know Your Data Inside Out
Make sure you’re well-versed in the types of datasets mentioned in the job description, especially Economics data. Brush up on your knowledge of macroeconomic indicators, time-series data, and how they impact business decisions. This will help you demonstrate your expertise and show that you understand the role's requirements.
✨Showcase Your Technical Skills
Prepare to discuss your hands-on experience with Python and any other relevant programming languages. Be ready to provide examples of scalable data solutions or ETL pipelines you've built. Highlight your familiarity with workflow orchestration and monitoring frameworks, as these are crucial for the role.
✨Communicate Clearly and Collaboratively
Since this role involves working closely with various teams, practice articulating your thoughts clearly. Think about how you can convey complex technical concepts in a way that non-technical stakeholders can understand. This will showcase your strong communication skills and ability to collaborate effectively.
✨Prepare for Problem-Solving Scenarios
Expect to face questions that assess your problem-solving abilities. Prepare to discuss past experiences where you identified workflow efficiencies or modernised legacy systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
