We are building a world-class data platform to support systematic trading across 10 global exchanges. This role will lead the Data Engineering team responsible for ingesting processing storing and serving all market reference and alternative data with low latency and high reliability. You will also own the architecture and evolution of our Feature Store which powers our live trading systems and research pipeline.
This is a hands-on technical leadership position with significant ownership and influence over our trading technology stack.
Key Responsibilities
- Drive end-to-end delivery of core data engineering initiatives including market data platforms real-time and batch pipelines feature stores and scalable storage and processing systems.
- Lead and mentor the Data Engineering team; translate business and research needs into clear roadmaps execution plans and engineering standards (code quality testing CI/CD).
- Own data ingestion and processing for live and historical datasets defining SLAs data quality metrics monitoring schemas and governance.
- Design and operate feature generation and serving platforms ensuring low-latency production pipelines reproducibility versioning and lineage.
- Build and maintain data infrastructure and tooling including collectors ingestion services metadata/catalog systems and compute workflows.
- Collaborate closely with researchers product and engineering teams as well as compliance and risk to enable fast experimentation and reliable production deployment.
Qualifications :
- 6 years in Data Engineering with at least 2 years in a lead role.
- Prior experience in trading HFT systematic hedge fund crypto exchange or similar (very important).
- Profound expertise in diverse types of market data.
- Strong experience with streaming systems columnar storage and distributed compute (e.g. Kafka/Redpanda Parquet/ORC Spark/Flink/Ray).
- Proficiency in Python and at least one systems language (Rust Go or C).
- Proven ownership of data pipelines in latency-sensitive or production-critical environments.
- Ability to work independently break down ambiguous problems and deliver clear outcomes.
- Strong communication skills and a leadership mindset including mentoring setting standards and documenting decisions.
Nice to Have
- Experience building or operating a Feature Store.
- Background supporting quant research (alphas signals features).
- Familiarity with time-series databases.
- Experience onboarding multiple exchanges or large-scale market datasets.
- Understanding of market data vendor challenges exchange-specific nuances entitlements and data quality.
Additional Information :
What we offer:
- Working in a modern international technology company without bureaucracy legacy systems or technical debt.
- Excellent opportunities for professional growth and self-realization.
- We work remotely from anywhere in the world with a flexible schedule.
- We offer compensation for health insurance sports activities and professional training.
Remote Work :
Yes
Employment Type :
Full-time
We are building a world-class data platform to support systematic trading across 10 global exchanges. This role will lead the Data Engineering team responsible for ingesting processing storing and serving all market reference and alternative data with low latency and high reliability. You will also ...
We are building a world-class data platform to support systematic trading across 10 global exchanges. This role will lead the Data Engineering team responsible for ingesting processing storing and serving all market reference and alternative data with low latency and high reliability. You will also own the architecture and evolution of our Feature Store which powers our live trading systems and research pipeline.
This is a hands-on technical leadership position with significant ownership and influence over our trading technology stack.
Key Responsibilities
- Drive end-to-end delivery of core data engineering initiatives including market data platforms real-time and batch pipelines feature stores and scalable storage and processing systems.
- Lead and mentor the Data Engineering team; translate business and research needs into clear roadmaps execution plans and engineering standards (code quality testing CI/CD).
- Own data ingestion and processing for live and historical datasets defining SLAs data quality metrics monitoring schemas and governance.
- Design and operate feature generation and serving platforms ensuring low-latency production pipelines reproducibility versioning and lineage.
- Build and maintain data infrastructure and tooling including collectors ingestion services metadata/catalog systems and compute workflows.
- Collaborate closely with researchers product and engineering teams as well as compliance and risk to enable fast experimentation and reliable production deployment.
Qualifications :
- 6 years in Data Engineering with at least 2 years in a lead role.
- Prior experience in trading HFT systematic hedge fund crypto exchange or similar (very important).
- Profound expertise in diverse types of market data.
- Strong experience with streaming systems columnar storage and distributed compute (e.g. Kafka/Redpanda Parquet/ORC Spark/Flink/Ray).
- Proficiency in Python and at least one systems language (Rust Go or C).
- Proven ownership of data pipelines in latency-sensitive or production-critical environments.
- Ability to work independently break down ambiguous problems and deliver clear outcomes.
- Strong communication skills and a leadership mindset including mentoring setting standards and documenting decisions.
Nice to Have
- Experience building or operating a Feature Store.
- Background supporting quant research (alphas signals features).
- Familiarity with time-series databases.
- Experience onboarding multiple exchanges or large-scale market datasets.
- Understanding of market data vendor challenges exchange-specific nuances entitlements and data quality.
Additional Information :
What we offer:
- Working in a modern international technology company without bureaucracy legacy systems or technical debt.
- Excellent opportunities for professional growth and self-realization.
- We work remotely from anywhere in the world with a flexible schedule.
- We offer compensation for health insurance sports activities and professional training.
Remote Work :
Yes
Employment Type :
Full-time
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