At a Glance
- Tasks: Lead the market data engineering team and define strategic vision for data architecture.
- Company: Join Glencore, a leader in commodities trading with a focus on innovation.
- Benefits: Competitive salary, career growth opportunities, and a collaborative work environment.
- Other info: Hands-on role with opportunities to work on cutting-edge technology.
- Why this job: Make a real impact by shaping market data solutions in a dynamic industry.
- Qualifications: Proven experience in market data platforms and strong leadership skills required.
The predicted salary is between 80000 - 100000 £ per year.
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 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 International AG
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 not only lead a talented team but also have the opportunity to shape the future of our market data capabilities in a fast-paced commodities environment. With a strong focus on employee growth, we provide ample opportunities for professional development and a supportive atmosphere that encourages hands-on involvement in cutting-edge technology.
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! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works in market data engineering. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects related to market data platforms. This is a great way to demonstrate your hands-on experience and technical prowess to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common market data engineering challenges. Think about how you would tackle issues like data ingestion and processing. Being ready to discuss these topics will show you're not just a candidate, but a problem-solver.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, applying directly can sometimes give you a leg up in the hiring process.
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, data ingestion, and team leadership. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of your past achievements in market data engineering and how you can contribute to our team at Glencore.
Showcase Your Technical Skills:Don’t forget to highlight your technical expertise! Mention your hands-on experience with programming languages like Python, and your familiarity with data pipelines and real-time processing. We love seeing candidates who can dive into the tech side of things!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss any important updates from us. Good luck!
How to prepare for a job interview at Glencore International AG
✨Know Your Market Data Inside Out
Before the interview, make sure you brush up on your knowledge of market data platforms, especially Zema. Understand how it integrates with ETRM systems and be ready to discuss your experience with real-time data ingestion and processing.
✨Showcase Your Leadership Skills
As a potential team lead, it's crucial to demonstrate your ability to create a collaborative environment. Prepare examples of how you've successfully led technical teams, resolved complex issues, and guided architectural decisions in previous roles.
✨Align with Stakeholder Needs
Be prepared to discuss how you’ve managed stakeholder relationships in the past. Highlight your communication skills and provide examples of how you’ve aligned priorities with different teams, such as Trading, Risk, and Quant Engineering.
✨Demonstrate Technical Proficiency
Since this role requires hands-on programming skills, be ready to talk about your experience with Python and data engineering concepts. You might even want to prepare for some technical questions or scenarios that test your problem-solving abilities in data pipeline optimisation.