Market Data Engineer

Who We Are

At Intropic
, we’re building the future of financial intelligence, where deep market expertise meets the power of AI. Founded in London’s financial centre of Canary Wharf, we exist to transform complex data into clarity, precision, and action. Our culture is shaped by truth‑seeking, velocity, and ownership, values that drive how we build, learn, and collaborate every day. We move fast, think independently, and hold ourselves to the highest standards of integrity and impact.

Here, curiosity isn’t just encouraged, it’s essential. If you’re driven by challenge, inspired by innovation, and ready to amplify your intelligence alongside a team of exceptional thinkers,
Intropic is where your ideas can truly compound.

We’re seeking a proactive and technically adept Market Data Engineer who thrives in building robust, low‑latency systems. If you're passionate about financial markets and skilled at developing real‑time data pipelines, we’d love to meet you.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Finance, or related field
• Proficiency in Python plus strong familiarity with C++ or Java
• Solid understanding of real‑time feed handling, message protocols, and distributed data architecture
• Hands‑on experience with market data sources (e.g., Bloomberg, Refinitiv) and familiarity with cloud platforms (e.g. AWS, GCP) and technologies like Kafka
• Skilled in building scalable data pipelines (ETL, streaming) and ensuring data quality, integrity, and performance
• Excellent attention to detail, problem‑solving mindset, and ability to manage tight SLAs
• Effective communicator with strong stakeholder collaboration skills

• Comfortable implementing monitoring, self‑service tools, and operational dashboards
• Experience in quant finance or working with trading and research teams
• Background in systems performance optimization and high‑throughput data environments

• Design, develop, and maintain real‑time and historical market data pipelines from various sources
• Ensure high data integrity and system availability while handling large‑scale data processing
• Monitor key metrics and build tools to streamline data access and operations
• Collaborate across product teams to align infrastructure with strategic needs
• Deliver clean, well‑tested, and maintainable code in a fast‑paced startup environment