Data Engineer for Systematic Trading role involves designing and building lakehouse-style data platforms to support research, risk, and live trading use cases.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Data Engineer
Systematic Trading
Hong Kong (Relocation & Sponsorship available)
We’re working with a top-tier global systematic trading firm building out a central data platform used directly by multiple live trading desks.
This role sits right at the intersection of data engineering, cloud infrastructure, and quantitative research. You’ll be building and evolving large-scale data pipelines that ingest, process, and serve high-volume market and trading data under real production constraints.
What you’ll be doing
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- Design and build lakehouse-style data platforms supporting research, risk, and live trading use cases
- Developing Python-based pipelines for batch and streaming workloads
- Working with Spark for large-scale processing and Kafka / Flink for real-time ingestion and stream processing
- Modelling and optimising data for high-concurrency analytical access (OLAP)
- Operating in a cloud-native AWS environment, with a strong focus on performance, data quality, and reliability
- Partnering closely with quants and traders to deliver production-grade data solutions
What they’re looking for
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- 3+ years building serious data platforms in production
- Strong Python and SQL (C++/Rust a plus, but not essential)
- Hands-on experience with Spark and at least one streaming technology (Kafka and/or Flink)
- Comfort working close to infrastructure and cloud services
- Autonomous, structured problem-solver who enjoys high-impact work
- Finance or trading exposure is helpful, but strong engineers from adjacent domains will be considered
This is a high-impact role with real ownership, strong engineering standards, and direct visibility into how data drives trading outcomes.
Please APPLY and I'll be in touch with more details.
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