Team Leader Data Engineering & Integration Commodities Data

Team Leader - Data Engineering & Integration - 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 responsible for onboarding modelling and maintaining data that are fit for purpose for our clients. More than 320000 business leaders rely on the real time financial information available on the Bloomberg Professional Service. Our products run on intelligence and insight provided by the Commodities Team. Our team of analysts provide valuable data and insights to key decision makers within the commodity markets.
We are responsible for the data management of datasets across Power and Gas Oil Carbon Agriculture and Metals. The team provides relevant timely and accurate data to empower customers to drive their analysis of commodity markets both pricing and fundamentals.
The Role:
This role will own the modernization stability and scalability of core commodities data manufacturing capabilities across reference data fundamentals curves spot and index prices and environmental datasets.
The successful candidate will manage a team responsible for improving commodities data pipelines integration patterns workflow architecture controls and operating models. They will reduce operational risk rationalize legacy workflows improve automation and ensure commodities datasets can be onboarded transformed validated monitored governed and delivered consistently across the ecosystem.
This role requires strong data management expertise practical engineering and integration awareness and the ability to partner effectively with Data Modelling Data Quality Product Engineering Content Acquisition Enablement and regional teams.
Well trust you to:

• 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 agreed 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 solutions remain governed explainable and supportable.
• 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.

Youll need to have:

• 3 years of formal people leadership experience or strong informal leadership
• Bachelors degree or equivalent preferably in Economics or Finance or related business / STEM field
• Experience leading or materially improving a data manufacturing data operations data pipeline workflow engineering or integration environment in a commodities market data financial data or similarly complex domain.
• Solid understanding of commodities data including reference data fundamentals curves spot prices index data pricing data environmental commodities or related market datasets.
• Experience designing improving or supporting complex data pipelines across ingestion transformation enrichment validation publication monitoring and exception management.
• Demonstrable ability to modernize legacy workflows and move teams toward scalable automated supportable and well-controlled operating models.
• Strong working knowledge of Python SQL orchestration tools workflow platforms automation frameworks observability and production support practices.
• Experience embedding data quality controls reconciliation completeness checks timeliness checks and exception workflows into production processes.
• Ability to work closely with data modelling teams on entity structures identifiers taxonomy rules metadata and workflow logic.
• Experience reducing operational risk through stronger controls monitoring documentation root-cause prevention and support models.
• Demonstrable ability to lead develop and coach a team while setting clear priorities and handling senior stakeholder expectations.
• Good communication skills with the ability to translate technical workflow and operational risk topics into clear business value.
• Experience evaluating or applying AI automation or workflow augmentation in a governed and supportable way would be advantageous.

Wed love to see:

• Experience or knowledge in the Bloomberg terminal and/or Bloomberg Data workflows
• Experience or strong curiosity about data modeling in addition to strong Excel and PowerPoint skills SQL experience and Coding experience
• Strong people leadership skills including coaching prioritization stakeholder management and building capability in technical data teams.
• Experience working closely with data modelling data quality engineering product acquisition and regional partners to deliver scalable data solutions.

If this sounds like you:Apply! If you think were a good match. Well get in touch to let you know the next steps!
If indicated please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture values and the people behind our success.

Required Experience:

Manager

Employment Type : Full Time
Experience: years
Vacancy: 1