Team Leader - Data Engineering & Integration

Bloomberg; Greater London; On-site; GBP 55,000 - 95,000; Full time

Job summary

Bloomberg London is seeking a senior leader to modernize commodities data pipelines and establish scalable, automated operating models. You will steer ingestion, transformation, validation, and publication across reference data, fundamentals, curves, and pricing datasets, partnering with data quality, modelling, and engineering teams to ensure robust, well-governed workflows.

You will coach a data management team, drive improvements in monitoring and controls, and balance modernization with

Qualifications

• 3+ years of formal people leadership experience, or strong informal leadership
• Bachelors degree or equivalent, preferably in Economics, Finance, or a related business / STEM field
• Experience leading or improving data manufacturing, data operations, data pipeline, workflow engineering, or integration environments
• Solid understanding of commodities data and related datasets
• Experience designing, improving, or supporting complex data pipelines
• Modernize legacy workflows and move teams toward scalable operating models
• Strong knowledge of Python, SQL, orchestration tools, workflow platforms, automation frameworks, observability, and production support
• Experience embedding data quality controls and exception workflows
• Ability to work with data modelling teams on entities, taxonomy, metadata, and workflow logic
• Experience reducing operational risk with controls, monitoring, and documentation
• Demonstrable ability to lead, develop, and coach a team with senior stakeholders
• Good communication to translate technical topics into business value
• Experience evaluating AI, automation, or workflow augmentation in a governed way would be advantageous
• Experience or knowledge in Bloomberg terminal, and Bloomberg Data workflows desirable
• Experience or strong curiosity about data modelling, Excel, PowerPoint, SQL, and coding
• Strong people leadership skills and stakeholder management
• Experience collaborating with data modelling, data quality, engineering, product, and regional partners

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, and opportunities for automation
• Re-engineer legacy workflows into scalable, resilient operating models
• Define standards for data manufacturing workflows, including documentation
• Partner with Data Quality to embed validation and controls into core workflows
• Work with Data Modelling to support entities, identifiers, taxonomy, and metadata
• Ensure datasets have clear ownership, controls, lineage, and auditability
• Improve monitoring, alerting, root-cause analysis, and recovery processes
• Reduce duplicate workflows and fragmentation across commodities data manufacturing
• Automate and standardize data handling, validation, and exception management
• Support vendor- and platform-driven changes, including schema migrations and API changes
• Identify opportunities to use AI-assisted tooling while remaining governed and explainable
• Manage a team of Data Management Professionals focused on data integration and scalable data manufacturing
• Set priorities and technical direction, balancing modernization and stability
• Build team capability in data pipelines, Python, SQL, orchestration, and production support
• Partner with Product, Engineering, Data Quality, Content Acquisition, Enablement, and regional teams
• Contribute to global Commodities strategy and operating-model evolution

Skills

Leadership

Stakeholder management

Communication

Problem solving

Team coaching

Education

Bachelor's degree or equivalent

Tools

Python

SQL

Orchestration tools

Workflow platforms

Automation frameworks

Excel

PowerPoint

Job description

Salary: £55,000 - 95,000 per year

Requirements:

• 3+ years of formal people leadership experience, or strong informal leadership
• Bachelors degree or equivalent, preferably in Economics, Finance, or a 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
• Experience or knowledge in the Bloomberg terminal, and/or Bloomberg Data workflows would be desirable
• Experience or strong curiosity about data modeling, along with 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

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 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

Technologies:

• AI
• API
• Excel
• Support
• Python
• SQL

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