# Senior Data Management Professional – Metadata, Data Engineering & Automation - Knowledge Graph Group at Bloomberg

Bloomberg is hiring a Senior Data Management Professional – Metadata, Data Engineering & Automation - Knowledge Graph Group in Dublin, Ireland. Level rates it Uses AI ●●○○; you can [apply on Level](https://jobsbylevel.com/go/ffc9e863-29db-422c-bf8f-05ef4f8dad1c?utm_medium=ai-agent).

AI Level 2, AI centrality 44 out of 100. Dublin, Ireland.

## Details

- Company: [Bloomberg](https://jobsbylevel.com/companies/bloomberg)
- AI level: AI Level 2 (score 44 out of 100)
- Location: Dublin, Ireland
- Posted: October 14, 2026
- Apply: https://jobsbylevel.com/go/ffc9e863-29db-422c-bf8f-05ef4f8dad1c?utm_medium=ai-agent

## Description

Our Team 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 and 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 that enhance our systems, products and processes. We are building a new Data capability in Dublin focused on metadata management, data quality, semantic modeling and workflow automation. The team will work closely with Bloomberg’s Knowledge Graph, Unified Field Management, Enterprise Data and Data License teams to improve how Bloomberg data is modeled, described, governed and delivered. Our work spans metadata platforms and products including UFM, XDM, BQL, Calc_Rt, Data License and Bloomberg’s broader semantic and knowledge-graph ecosystem. The goal is not simply to operate existing processes. We want to understand how the work functions today, identify recurring quality and operational problems, and build scalable solutions that improve efficiency, consistency and data quality. What’s the role? As a Senior Data Management Professional in Dublin, you will work at the intersection of data management, data engineering, metadata, data quality and semantic modeling. You will initially develop hands-on expertise across Bloomberg’s metadata and data-management ecosystem, learning how field metadata, APIs, models, datasets and Enterprise products are created, governed and consumed. You will work directly on real metadata, quality and onboarding workflows so that you understand their business purpose, dependencies and operational constraints. Automation starts with understanding the work: you will first learn the workflow, business rules, dependencies and exceptions before deciding what should be standardized, redesigned or automated. As your expertise grows, the role will shift toward ownership and improvement. You will take responsibility for workflows and projects, identify systemic quality issues, automate repetitive processes, improve controls and validation, and partner with Product and Engineering on more scalable approaches. This is deliberately a hybrid role. We are interested in people who may come from data management, data engineering, metadata, data quality or adjacent technical disciplines, provided they are comfortable moving between data analysis, modeling, automation, operational problem-solving and stakeholder engagement. We’ll trust you to: Develop working expertise across UFM, XDM, BQL, Calc_Rt, Data License and related metadata and semantic platforms. Own increasingly complex metadata, data-quality and dataset-onboarding work from requirements through validation, release and post-release remediation. Analyze data and metadata inventories to identify inconsistencies, gaps, dependencies and opportunities for standardization. Investigate data and metadata quality issues using profiling, validation, root-cause analysis and structured data analysis. Identify repetitive manual workflows and design automation ranging from lightweight scripts and validation tooling to reusable workflow tooling and integrations, choosing the appropriate technical approach for the problem. Build or improve validation, monitoring, reporting and change-impact processes that make data and metadata quality measurable. Align related concepts, classifications, enumerations and field definitions across metadata systems and contribute to semantic-modeling and metadata-alignment initiatives. Partner with Data Engineering and Engineering teams on tooling, services, APIs and workflow improvements. Work across Product, Data and Engineering teams to translate operational needs into metadata, quality controls and scalable technical solutions. Evaluate where AI-assisted or agent-assisted tooling can safely improve enrichment,

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/senior-data-management-professional-metadata-data-engineering-automation-knowledge-graph-group-at-bloomberg-14edf3

Source: https://jobsbylevel.com/jobs/senior-data-management-professional-metadata-data-engineering-automation-knowledge-graph-group-at-bloomberg-14edf3

## Cite this page

Level. https://jobsbylevel.com/jobs/senior-data-management-professional-metadata-data-engineering-automation-knowledge-graph-group-at-bloomberg-14edf3.

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