Senior Data Management Professional - Data Engineer - Economics Data

Senior Data Management Professional - Data Engineer - Economics Data

Location: London

Business Area: Data

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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, scalable, well structured, and ready to use.

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.

• 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.

• 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.

• 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.

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 .