At a Glance
- Tasks: Lead the market data engineering team and define Glencore’s market data strategy.
- Company: Join a leading global commodities company with a focus on innovation.
- Benefits: Competitive salary, career growth opportunities, and a collaborative work environment.
- Other info: Work closely with diverse teams and tackle complex challenges daily.
- Why this job: Make a real impact in the dynamic world of market data engineering.
- Qualifications: Experience in market data platforms and strong leadership skills required.
The predicted salary is between 80000 - 100000 € per year.
As the Market Data Engineering Team Lead, you will be responsible for defining and leading Glencore’s 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 day‑to‑day BAU operations, platform stability, and ongoing delivery challenges.
The ideal candidate disposes of:
- Lead the market data engineering team, creating a collaborative, delivery‑focused environment, while remaining sufficiently hands‑on 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, trade‑offs, 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 day‑to‑day 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 point‑to‑point 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.
Market Data Engineering Team Lead in London employer: Glencore
At Glencore, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. As the Market Data Engineering Team Lead, you will have the opportunity to shape our market data strategy while working alongside talented professionals in a supportive environment that prioritises employee growth and development. With a focus on cutting-edge technology and a commitment to operational excellence, Glencore provides a unique platform for meaningful contributions in the commodities trading sector.
StudySmarter Expert Advice🤫
We think this is how you could land Market Data Engineering Team Lead in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects that highlight your market data engineering expertise, make sure to share them during interviews. It’s a great way to demonstrate your hands-on experience and technical prowess.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your knowledge of market data platforms and be ready to discuss how you’d tackle real-world challenges. This shows you’re not just a theory buff but someone who can lead a team through complex issues.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a straightforward way to get your application noticed by the right people.
We think you need these skills to ace Market Data Engineering Team Lead in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Market Data Engineering Team Lead role. Highlight your experience with market data platforms, team leadership, and any relevant technical skills. We want to see how your background aligns with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about market data engineering and how you can contribute to our team. Be sure to mention specific projects or achievements that relate to the job description.
Showcase Your Technical Skills:Since this role requires hands-on technical expertise, don’t shy away from showcasing your programming skills and experience with data pipelines. We love seeing examples of how you've tackled complex issues in past roles!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Glencore
✨Know Your Market Data Inside Out
Make sure you brush up on your knowledge of market data platforms, especially Zema. Be ready to discuss how you've designed and built similar systems in the past, and think about specific examples where you've optimised data pipelines or tackled complex issues.
✨Showcase Your Leadership Skills
As a team lead, you'll need to demonstrate your ability to create a collaborative environment. Prepare to share experiences where you've successfully led technical teams, guided architectural decisions, and resolved conflicts. Highlight your hands-on approach to leadership.
✨Communicate Clearly with Stakeholders
Effective communication is key in this role. Think about how you've managed stakeholder relationships in the past. Be ready to discuss how you've communicated priorities, trade-offs, and delivery challenges to different teams, ensuring everyone is aligned.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during your interview. Brush up on programming concepts, particularly Python, and be prepared to discuss your experience with real-time data ingestion and processing. Show that you can challenge approaches and set engineering standards.
