Full-time position responsible for building and operating the data infrastructure that underpins our trading and research systems. You will own data pipelines end-to-end — from raw ingestion through transformation, quality assurance, and delivery to downstream consumers. This is a hands-on engineering role, not a management position.

• Design, build, and maintain high-throughput data pipelines processing petabyte-scale market data, execution logs, alternative data, and reference data • Operate and evolve our analytical data platform — columnar stores, workflow orchestration, and custom tooling • Ingest and normalize data from exchanges, vendors, and internal systems into consistent, queryable formats • Implement data quality checks, lineage tracking, and monitoring to guarantee correctness and freshness • Optimize storage layouts, query performance, and pipeline latency for both batch and near-real-time workloads • Build and maintain data infrastructure supporting AI/ML workflows — training data preparation, feature pipelines, and model serving • Collaborate directly with quantitative researchers, risk managers, and infrastructure teams to translate data requirements into reliable code and infrastructure • Own the full lifecycle: capacity planning, schema evolution, incident response, and documentation

• Degree in Computer Science, Engineering, Mathematics, or Physics from a top-tier university • 5+ years of hands-on data engineering in a production environment handling terabyte-to-petabyte scale data • Strong proficiency in Python — production-grade code, not just glue scripts • Strong proficiency in at least one statically typed language (C++ preferred) • Strong SQL skills and experience operating columnar/OLAP databases at scale • Linux proficiency — comfortable profiling performance, managing processes, and debugging production systems • Experience with workflow orchestration and building data pipelines supporting AI/ML workloads • Solid understanding of distributed systems - partitioning, replication, consistency trade-offs, failure modes • Active use of AI-assisted development tools as part of daily engineering workflow

• Excellent communication skills in English

1차테스트 및 실무면접 ＞ 2차테스트 ＞ 최종면접

Please submit your English CV