Team Leader - Data Engineering & Integration - Commodities Data

In this role you lead the Commodities Data Team to modernize and scale data manufacturing across reference data, fundamentals, curves, and pricing datasets. You will partner with data, product, and engineering teams to deliver robust, automated pipelines with strong controls. You’ll drive operational excellence, reduce risk, and mentor a high-performing team shaping Bloomberg’s commodity data capabilities. You’ll act as a bridge between technical delivery and business value in a fast, data-driven environment.

• Lead modernization of commodities data pipelines across reference data, fundamentals, curves, pricing, index data, and environmental datasets
• Establish scalable ingestion, transformation, enrichment, validation, publication, monitoring, and exception patterns
• Identify and remove duplication, fragility, and manual interventions; automate and consolidate workflows
• Re-engineer legacy workflows into scalable, controlled operating models
• Define standards for data manufacturing workflows and documentation
• Partner with Data Quality to embed validation, completeness, timeliness, reconciliation, and exception controls
• Ensure pipelines support entities, identifiers, taxonomies, metadata, and lifecycle rules
• Deliver datasets with clear ownership, lineage, controls, documentation, and auditability
• Improve monitoring, alerting, root-cause analysis, and recovery processes to reduce risk
• Automate data handling, enrichment, validation, and exception management; ensure governance
• Support vendor- and platform-driven changes (schema, API migrations, taxonomy updates)
• Identify opportunities for AI-assisted tooling to reduce manual work with governance and explainability
• Manage a team focusing on data integration, workflow engineering, automation, and production support
• Set priorities and technical direction balancing modernization with production stability
• Build team capability in Python, SQL, orchestration, automation, observability, and production support
• Partner with Product, Engineering, Data Modelling, Data Quality, Content Acquisition, Enablement, and regional teams
• Contribute to global Commodities strategy, workflow standards, and operating-model evolution

• 3+ years of formal people leadership experience or strong informal leadership
• Bachelor's degree or equivalent in Economics, Finance, or related field
• Experience leading data manufacturing, data operations, or data integration in commodities or financial data
• Solid understanding of commodities datasets (reference data, fundamentals, curves, spot and index prices, environmental data)
• Experience designing or improving complex data pipelines (ingestion, transformation, enrichment, validation, monitoring, exception management)
• Ability to modernize legacy workflows toward scalable, automated operating models
• Strong Python, SQL, orchestration tools, workflow platforms, automation, observability, and production support knowledge
• Experience embedding data quality controls, reconciliation, timeliness, and exception workflows
• Ability to collaborate with data modelling teams on entities, taxonomy, metadata, and workflow logic
• Experience reducing operational risk through monitoring, documentation, and support models
• Proven ability to lead, develop, and coach a team and manage senior stakeholder expectations
• Good communication skills translating technical topics into business value
• Experience evaluating AI or automation in a governed and supportable way (advantageous)

• leadership
• stakeholder management
• coaching and mentoring
• Python
• SQL
• orchestration tools