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 You’ll drive end-to-end delivery of key data engineering projects such as : A unified platform for collecting and serving market data. Real‑time and batch pipelines that transform raw data into usable features. A central store for offline, online and streaming features. Frameworks to ensure data quality, consistency and reliability. Tools for managing historical datasets and replaying data for research. Scalable storage and processing systems used by researchers and production systems. Lead & Deliver Grow and mentor a Data Engineering team. Translate business and research needs into clear plans and roadmaps. Set engineering standards around code quality, testing and CI/CD. Drive execution of the team’s long‑term data platform strategy. Own Data Engineering Oversee ingestion and processing of live and historical datasets. Define SLAs, data quality metrics and monitoring. Manage schemas, storage formats and dataset governance. Standardize data representations across different sources. Feature Platform Ownership Design architectures for generating and serving features. Maintain low‑latency pipelines used in production systems. Oversee intra‑day feature computation and transformations. Ensure reproducibility, versioning and lineage across the feature stack. Infrastructure & Tooling Build and maintain data collectors and ingestion services. Manage scalable storage solutions for research and production use. Own metadata and cataloging tools. Develop compute workflows for feature updates and model support. Collaboration Work closely with researchers to enable fast experimentation. Partner with engineering teams to ensure smooth integration into production systems. Collaborate with compliance and risk functions on governance and auditability. 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. Profound expertise in diverse types of market data. Deep expertise in : Streaming systems (Kafka, Redpanda, Pulsar, Kinesis or equivalent) Columnar storage (Parquet, ORC) Distributed compute (Spark, Flink, Ray, Dask) Python, Rust, Go or C Proven ownership of data pipelines supporting latency‑sensitive environments. Strong ownership mentality and ability to work independently. Ability to break down ambiguous problems into clear deliverables. Excellent written and verbal communication. Leadership mindset: developing engineers, setting standards, documenting decisions. Would be a plus Built a Feature Store. Experience supporting quant researchers (alphas, signals, features). Time‑series databases. Managed onboarding of multiple exchanges or large‑scale datasets. Comprehensive awareness of common challenges associated with various market data vendors, data types and formats. Demonstrated experience in managing exchange‑specific intricacies, data entitlements and data quality issues. 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 : No Employment Type : Full‑time Department / Functional Area : Data Engineering Vacancy : 1 #J-18808-Ljbffr