At a Glance
- Tasks: Drive data quality strategy and ensure Economics datasets meet client expectations.
- Company: Bloomberg, a leader in data-driven technology and analytics.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Join a diverse team committed to continuous improvement and accountability.
- Why this job: Make a real impact on data quality in a dynamic, innovative environment.
- Qualifications: Bachelor's degree and 4+ years in data management or related fields.
The predicted salary is between 60000 - 80000 £ per year.
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.
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, complete, transparent, and ready to use.
The Economics Data team is looking for a Senior Data Management Professional – Data Quality to define and drive the quality strategy for Economics data products. This role is focused on setting quality standards, defining fit‑for‑purpose metrics, strengthening controls, improving issue management, and ensuring data quality is measured transparently across tools, processes, and datasets.
You will work closely with Data, Engineering, Product, Vendors, and Domain teams to ensure Economics datasets meet client expectations, support commercial priorities, and are governed through clear controls, ownership, and measurable outcomes.
We'll trust you to:
- Define and own the data quality vision, strategy, and roadmap for Economics datasets.
- Set fit‑for‑purpose quality metrics, SLAs, targets, and standards aligned to client, product, commercial, and regulatory needs.
- Design data quality controls across completeness, accuracy, timeliness, consistency, schema change, anomaly detection, and data integrity.
- Use data profiling, root‑cause analysis, and trend analysis to identify quality risks and drive sustainable remediation.
- Own the data quality issue management framework, including logging, triage, prioritization, accountability, remediation tracking, and closure.
- Partner with Engineering to translate quality needs into pipeline controls, monitoring, tooling, observability, and automation requirements.
- Represent Economics Data in lifecycle governance, policy implementation, and quality framework discussions.
- Define guardrails for automated or AI‑assisted quality workflows, including imputation, validation, exception handling, and downstream flagging.
- Improve transparency of tools, processes, and data health through dashboards, reporting, and regular communication to senior partners.
- Work with Vendors, Product, Engineering, and Data teams to resolve quality issues at source and prevent recurrence.
- Influence data governance, metadata, lineage, data modelling, and lifecycle management practices across Economics datasets.
- Promote a culture of accountability, continuous improvement, automation, and client‑focused quality.
You’ll need to have:
- A bachelor’s degree or above in Economics, Statistics, Computer Science, Mathematics, Engineering, Quantitative Finance, or equivalent experience.
- 4+ years of experience in data management, data quality, data operations, data governance, or data product ownership.
- Solid experience defining quality metrics, SLAs, controls, KPIs, issue management processes, and remediation frameworks.
- Experience working across the full data lifecycle, including ingestion, normalization, enrichment, modelling, quality control, distribution, and monitoring.
- Strong analytical skills, including data profiling, root‑cause analysis, trend analysis, and evidence‑based decision‑making.
- Technical grounding in Python, SQL, data analysis, data visualization, or similar tools used to assess and improve data quality.
- Experience translating business and client needs into clear requirements for Engineering, Product, vendors, or operational teams.
- Good understanding of data governance, data lifecycle management, data modelling, metadata, and data integrity principles.
- Superb communication and stakeholder management skills, with the ability to influence senior partners and align distributed teams.
- Ability to operate through ambiguity, set direction, prioritize effectively, and drive measurable quality improvements.
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 designing quality strategies in complex, regulated, or high‑control environments.
- Experience using AI, machine learning, anomaly detection, statistical methods, or automation to improve data quality workflows.
- Experience defining validation frameworks for automated, AI‑assisted, or imputed data outputs.
- Experience with observability tools, workflow orchestration, issue tracking, data catalogues, lineage, metadata management, or modern DataOps practices.
- Project management experience with Agile delivery, backlog management, JIRA, QlikSense, or similar tools.
- Understanding of Causal Inference.
- CDMP certification, or progress toward it, is a plus.
If this sounds like you: Apply! If you think we’re a good match. We’ll get in touch to let you know the next steps!
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.
Senior Data Management Professional - Data Quality - Economics Data London, GBR employer: Bloomberg L.P.
Bloomberg is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong commitment to employee growth, we provide ample opportunities for professional development and encourage a culture of accountability and continuous improvement. Our focus on diversity and inclusion ensures that every voice is valued, making Bloomberg not just a workplace, but a community where you can thrive and make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Management Professional - Data Quality - Economics Data London, GBR
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Bloomberg. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Prepare for interviews by diving deep into data quality concepts. Brush up on your knowledge of metrics and controls, and be ready to discuss how you can enhance Economics datasets.
✨Tip Number 3
Showcase your analytical skills! Bring examples of how you've tackled data quality issues in the past. Real-life stories resonate more than just theory.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Senior Data Management Professional - Data Quality - Economics Data London, GBR
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data management and quality. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Showcase Your Analytical Skills:Since this role is all about data quality, be sure to include examples of your analytical prowess. Whether it’s through data profiling or trend analysis, we love seeing how you’ve tackled data challenges in the past.
Be Clear and Concise:When writing your application, clarity is key! Use straightforward language and get straight to the point. We appreciate a well-structured application that makes it easy for us to see your qualifications.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details 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
Before the interview, dive deep into the types of Economics datasets you'll be working with. Familiarise yourself with macroeconomic indicators, government data, and time-series analysis. Being able to discuss specific examples will show your expertise and passion for data quality.
✨Showcase Your Analytical Skills
Prepare to demonstrate your analytical prowess during the interview. Bring examples of how you've used data profiling, root-cause analysis, or trend analysis in past roles. This will highlight your ability to identify quality risks and implement effective solutions.
✨Communicate Clearly and Confidently
Strong communication is key, especially when discussing complex data issues. Practice explaining technical concepts in simple terms, as you’ll need to influence senior partners and align teams. Clear communication can set you apart from other candidates.
✨Be Ready to Discuss Quality Metrics
Since the role focuses on defining quality standards, come prepared to talk about your experience with SLAs, KPIs, and issue management processes. Think of specific metrics you've implemented in previous roles and how they improved data quality.