About this role
Salary: £55,000 - 95,000 per year
Requirements: 3+ years of formal people leadership experience, or strong informal leadershipBachelors degree or equivalent, preferably in Economics, Finance, or a related business / STEM fieldExperience 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 domainSolid understanding of commodities data, including reference data, fundamentals, curves, spot prices, index data, pricing data, environmental commodities, or related market datasetsExperience designing, improving, or supporting complex data pipelines across ingestion, transformation, enrichment, validation, publication, monitoring, and exception managementDemonstrable ability to modernize legacy workflows and move teams toward scalable, automated, supportable, and well-controlled operating modelsStrong working knowledge of Python, SQL, orchestration tools, workflow platforms, automation frameworks, observability, and production support practicesExperience embedding data quality controls, reconciliation, completeness checks, timeliness checks, and exception workflows into production processesAbility to work closely with data modelling teams on entity structures, identifiers, taxonomy rules, metadata, and workflow logicExperience reducing operational risk through stronger controls, monitoring, documentation, root-cause prevention, and support modelsDemonstrable ability to lead, develop, and coach a team while setting clear priorities and handling senior stakeholder expectationsGood communication skills, with the ability to translate technical, workflow, and operational risk topics into clear business valueExperience evaluating or applying AI, automation, or workflow augmentation in a governed and supportable way would be advantageousExperience or knowledge in the Bloomberg terminal, and/or Bloomberg Data workflows would be desirableExperience or strong curiosity about data modeling, along with strong Excel and PowerPoint skills, SQL experience, and coding experienceStrong people leadership skills, including coaching, prioritization, stakeholder management, and building capability in technical data teamsExperience working closely with data modelling, data quality, engineering, product, acquisition, and regional partners to deliver scalable data solutions Responsibilities: Lead modernization of commodities data pipelines across reference data, fundamentals, curves, pricing, index data, and environmental datasetsEstablish scalable patterns for ingestion, transformation, enrichment, validation, publication, monitoring, and exception managementAssess existing workflows to identify duplication, fragility, inconsistent logic, manual intervention, and opportunities for automation or consolidationRe-engineer legacy workflows into scalable, resilient, supportable, and well-controlled operating modelsDefine standards for data manufacturing workflows, including documentationPartner with Data Quality to embed validation, completeness, timeliness, reconciliation, and exception controls into core workflowsWork with Data Modelling to ensure pipelines support agreed entities, identifiers, relationships, taxonomies, metadata, and lifecycle rulesEnsure datasets are delivered with clear ownership, controls, lineage, documentation, support models, and auditabilityImprove monitoring, alerting, root-cause analysis, recovery processes, and preventative controls to reduce operational riskReduce duplicate workflows, redundant processes, manual workarounds, and fragmented ownership across commodities data manufacturingAutomate and standardize data handling, enrichment, validation, exception management, monitoring, and recovery processesSupport vendor- and platform-driven change, including schema changes, API migrations, delivery format changes, taxonomy updates, and workflow migrationsIdentify 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 supportableManage a team of Data Management Professionals focused on data integration, workflow engineering, automation, operational stability, and scalable commodities data manufacturingSet clear priorities and technical direction, balancing modernization, production stability, partner needs, and business-as-usual deliveryBuild team capability in data pipelines, integration patterns, Python, SQL, orchestration, automation, observability, controls, and production supportPartner with Product, Engineering, Data Modelling, Data Quality, Content Acquisition, Enablement, and regional teams to deliver business-aligned outcomesContribute to global Commodities strategy, workflow standards, integration principles, and operating-model evolution Technologies: AIAPIExcelSupportPythonSQL More:
Bloombergs Data business is focused on delivering data, news, and analytics quickly and accurately through innovative technology. Our Commodities Data Team is responsible for onboarding, modelling, and maintaining data that is fit for purpose for our clients, covering Power and Gas, Oil, Carbon, Agriculture, and Metals. The role is based in London and sits within our Data business area. We support more than 320,000 business leaders who rely on the Bloomberg Professional Service, and our team provides relevant, timely, and accurate data to help customers analyze commodity markets, pricing, and fundamentals. We also share insights and perspectives through our podcast series, offering a look into our culture, values, and the people behind our success.
last updated 40 week of 2026