
at Glencore
CommoditiesPosted 8 days ago
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**Market Data Engineering Team Lead** - Lead market data engineering team, driving strategy and delivery - Define and own market data architecture, ingest, normalise, control, and distribute data - Manage Zema platform operations, integrations, and change activity - Liaise with stakeholders, ensure data meets analytical and control requirements - 7+ years' experience in market data engineering, leading teams, and delivering platforms - Proven skills in Python-based services, data pipelines, and real-time market data processing - Ideal candidates have experience in commodities trading or financial services tech environments - Apply by [June 25, 2026]
- Compensation
- Not specified GBP
- City
- London
- Country
- United Kingdom
Currency: £ (GBP)
Full Job Description
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- Market Data Engineering Team Lead
Market Data Engineering Team Lead
- Full time
- London, Greater London, United Kingdom
- Market Data
Summary
In details, the position encompasses duties and responsibilities as follows:
As the Market Data Engineering Team Lead, you will be responsible for defining and leading Glencores market data capability across commodities, ensuring reliable, consistent ingestion, normalisation, control and distribution of market data to downstream risk and other enterprise systems. A key responsibility will be setting the market data engineering strategy and delivering the target market data architecture, including a Unified Data Format (UDF) that abstracts vendor complexity while supporting batch and streaming data use cases.
The role also owns the future state market data platform from a technology and operational perspective, including integration with ETRM adapters and downstream systems, with accountability for daytoday BAU operations, platform stability, and ongoing delivery challenges.
The ideal candidate disposes of:
- Lead the market data engineering team, creating a collaborative, deliveryfocused environment, while remaining sufficiently handson to guide technical decisions and unblock complex issues when required.
- Define and own the strategic vision and roadmap for market data, aligning priorities with Trading, Risk, Quant, Operations, and Technology stakeholders
- Act as the senior Subject Matter Expert (SME) and defines architectural leadership for market data platforms, and distribution across Glencore.
- Manage stakeholder relationships effectively, communicating clearly around priorities, tradeoffs, and delivery challenges.
- Partner closely with Quant Engineering teams, ensuring market data platforms, data models, and interfaces effectively support quantitative models, analytics, and downstream risk use cases.
- Own the Zema platform, including daytoday BAU operations, incident management, prioritisation of issues, and coordination of change activity.
- Own and manage Zema integrations into ETRM systems via adapters, ensuring reliable data flows and clearly defined interfaces.
- Liaise with Quant Engineering, Trading, Risk, and Technology teams to ensure market data solutions meet analytical, valuation, and control requirements.
- Provide senior oversight and escalation support for market data issues impacting downstream risk and other systems.
Skills:
- Proven experience designing and building curated market data distribution platforms for Trading, Quant, and Risk use cases.
- Experience leading technical teams delivering market data and data platform solutions, with the ability to guide architecture, design, and implementation decisions.
- Strong understanding of market data ingestion, processing, and distribution across batch and real-time processing models.
- Demonstrated ability to optimise data pipelines for cost, performance, scalability, resilience, and reproducibility.
- Hands-on ability of programming and data engineering concepts (e.g. Python-based services and data pipelines), sufficient to review designs, challenge approaches, and set engineering standards.
- Hands-on experience with real-time market data ingestion and processing, supporting near-real-time downstream consumption.
- Proven experience owning and operating market data platforms such as Zema, including BAU accountability, incident management, and integration into ETRM systems.
- Experience working closely with Quant Engineering or analytics teams, supporting data requirements for models, valuation, and risk systems.
- Strong background in designing and delivering data services supporting trading, risk, and operational processes.
- Experience with unified or enterprise-standard data models and reducing pointtopoint integrations.
- Solid understanding of ETL/ELT patterns, data quality controls, and operational support models.
- Ideally experience working within commodities trading or financial services technology environments.
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