Senior Data Management Professional Data Quality Economics Data
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Job Summary
Senior Data Management Professional - Data Quality - Economics Data
Location
London
Business Area
Data
Ref #
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 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 complete transparent and ready to use.
Whats the role
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.
Well 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.
Youll need to have:
- A bachelors 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.
Wed 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 were a good match. Well get in touch to let you know the next steps!
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Required Experience:
Senior IC
About Company
Bloomberg is the world's primary distributor of financial data and a top news provider of the 21st century. A global information and technology company, we use our dynamic network of data, ideas and analysis to solve difficult problems every day. Our customers around the world rely on ... View more
