Head of Commodities Data Engineering & Pipelines

Bloomberg; Greater London; On-site; GBP 100,000 - 140,000; Full time

Job summary

Bloomberg in London is seeking a Senior Data Management Leader to own the modernization, stability, and scalability of commodities data manufacturing capabilities. You will lead a team responsible for improving pipelines, integration patterns, and operating models across reference data, fundamentals, curves, prices, and environmental datasets.

The role requires strong data management expertise, practical engineering and integration awareness, and the ability to partner with Data Modelling, Data

Qualifications

• 3+ years of formal people leadership experience
• Bachelor's degree or equivalent in Economics or Finance or related field
• Experience leading data manufacturing, data operations, data pipeline, or integration environments in commodities/financial data
• Solid understanding of commodities data including reference data, fundamentals, curves, spot prices, or pricing data
• Experience designing or supporting complex data pipelines across ingestion, transformation, enrichment, validation, publication, monitoring, and exception management
• Demonstrated ability to modernize legacy workflows toward scalable, automated operating models
• Strong knowledge of Python, SQL, orchestration tools, automation, observability, and production support practices
• Experience embedding data quality controls into production processes
• Ability to work with data modelling teams on entities, identifiers, taxonomy rules, metadata, and workflow logic

Responsibilities

• Lead modernization of commodities data pipelines across reference data, fundamentals, curves, pricing, index data, and environmental datasets.
• Establish scalable patterns for ingestion, transformation, enrichment, validation, publication, monitoring, and exception management.
• Assess existing workflows to identify duplication, fragility, inconsistent logic, manual intervention, and opportunities for automation or consolidation.
• Re-engineer legacy workflows into scalable, resilient, supportable, and well-controlled operating models.
• Define standards for data manufacturing workflows, including documentation.
• Partner with Data Quality to embed validation, completeness, timeliness, reconciliation, and exception controls into core workflows.
• Work with Data Modelling to ensure pipelines support entities, identifiers, relationships, taxonomies, metadata, and lifecycle rules.
• Ensure datasets are delivered with clear ownership, controls, lineage, documentation, support models, and auditability.
• Improve monitoring, alerting, root-cause analysis, recovery processes, and preventative controls to reduce operational risk.
• Reduce duplicate workflows, redundant processes, manual workarounds, and fragmented ownership across commodities data manufacturing.
• Automate and standardize data handling, enrichment, validation, exception management, monitoring, and recovery processes.
• Support vendor- and platform-driven change, including schema changes, API migrations, delivery format changes, taxonomy updates, and workflow migrations.
• Identify practical opportunities to use AI-assisted tooling and automation to reduce manual mapping, validation, documentation, exception handling, and operational triage while ensuring governed solutions.
• Manage a team of Data Management Professionals focused on data integration, workflow engineering, automation, operational stability, and scalable commodities data manufacturing.
• Set clear priorities and technical direction, balancing modernization, production stability, partner needs, and business-as-usual delivery.
• Build team capability in data pipelines, integration patterns, Python, SQL, orchestration, automation, observability, controls, and production support.
• Partner with Product, Engineering, Data Modelling, Data Quality, Content Acquisition, Enablement, and regional teams to deliver business-aligned outcomes.
• Contribute to global Commodities strategy, workflow standards, integration principles, and operating-model evolution.

Skills

Python

SQL

Orchestration tools

Data pipelines

Data quality controls

Stakeholder management

Team leadership

Education

Bachelor's degree or equivalent in Economics/Finance or related field

Tools

Bloomberg Terminal

Excel

PowerPoint

Job description

Bloomberg in London is seeking a Senior Data Management Leader to own the modernization, stability, and scalability of commodities data manufacturing capabilities. You will lead a team responsible for improving pipelines, integration patterns, and operating models across reference data, fundamentals, curves, prices, and environmental datasets.

The role requires strong data management expertise, practical engineering and integration awareness, and the ability to partner with Data Modelling, Data