Senior Data Management Professional Data Engineer Commodities Data
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Job Summary
Senior Data Management Professional - Data Engineer - Commodities 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 Commodities Data team is looking for a highly experienced Senior Data Management Professional to help lead the next generation of our data platform. This role requires a strong data engineering foundation combined with deep ownership of data quality where quality is built directly into pipelines systems and architecture rather than managed as a separate function. This role is designed for a top-tier individual contributor who thrives in complex environments and consistently delivers high-impact scalable solutions.
The Role:
You will be responsible for designing and evolving data systems that power Tier 1 datasets improving reliability reducing technical debt and modernizing legacy workflows. This includes building advanced ETL pipelines implementing intelligent automation and developing robust data quality controls and monitoring frameworks to ensure data accuracy completeness and timeliness.
In addition you will play a key role in defining and delivering the data quality vision for our datasets. This includes evolving fit-for-purpose quality metrics understanding how clients consume data across Bloomberg products and aligning data with both client needs and Bloombergs commercial strategy. You will also influence data governance practices and lifecycle management across teams to ensure long-term data integrity and scalability.
You will collaborate closely with Product Engineering and domain experts to define and execute on strategic data addition to hands-on development you will act as a technical leader within the team by owning end-to-end solutions influencing architecture decisions and mentoring others.
We are looking for someone who operates at a high bar of technical excellence takes ownership of both data systems and data quality outcomes and uses modern technologies including AI and machine learning to enhance data workflows and extract additional value from our datasets.
Well trust you to:
- Build and maintain highly scalable resilient and observable data pipelines supporting critical Commodities datasets
- Modernize 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 standard methodologies 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 set the standard for technical execution design thinking and engineering rigor
Youll need to have:
- A bachelors degree or above in Statistics Computer Science Quantitative Finance or other STEM related field or degree-equivalent qualifications
- 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 analyze refactor and modernize 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.
*Please note: years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
Wed love to see:
- Bloomberg Terminal BQL Enterprise or Bloomberg data workflow experience.
- Experience productionizing 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 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
