What You’ll Be Doing

• Build and operate high-throughput Java pipelines for public market data, including trades, best bid and offer (BBO), tickers, funding rates, and L2/full order-book data from exchange REST and WebSocket APIs.

• Build and operate pipelines for proprietary trading data, including orders, fills, positions, balances, risk, and other events delivered through Kafka and internal integrations.

• Own ingestion, parsing, normalization, sequencing, validation, recovery, storage, and data access, with a strong focus on correctness, reliability, and performance.

• Onboard new exchanges and internal data sources, handling authentication, rate limits, disconnects, resubscription, snapshots and deltas, protocol changes, schema evolution, reconciliation, and access control.

• Build real-time and historical data paths using technologies such as Chronicle Queue, Kafka, relational and time-series databases, Apache Iceberg, Parquet, and ClickHouse. Own schema design, partitioning, retention, and query performance.

• Develop and operate data-access services and APIs, including routing, service discovery, high availability, failover, authorization for proprietary data, and backward compatibility for downstream clients.

• Maintain platform stability through monitoring, alerting, capacity management, data-quality checks, reconciliation, incident response, post-incident follow-through, and reproducible runbooks. Participate in the on-call rotation and respond to PagerDuty incidents.

• Support trading desks, quantitative researchers, and analytics users with data access, source onboarding, query support, and Java/Python client libraries.

• Maintain and improve the existing production platform while delivering safe, incremental migrations toward Kafka, ClickHouse, Iceberg, and Kubernetes through parallel runs, reconciliation, and controlled cutovers.

• Use AI coding assistants and LLM tooling responsibly to accelerate development, debugging, and data operations, and help the team adopt effective AI-native workflows.

What We Look For In You

• Bachelor’s degree or above in Computer Science, Engineering, or a related quantitative field.

• 5+ years of hands-on experience in software engineering, market-data engineering, trading systems, or data-platform engineering.

• Strong production Java performance-tuning skills, including JVM and concurrency fundamentals, profiling, garbage collection and allocation behavior, and diagnosing thread and I/O bottlenecks.

• Hands-on experience building and operating real-time pipelines or data-serving systems for exchange market data, tick/order-book data, or proprietary trading data such as orders, fills, positions, balances, and risk.

• Experience building and operating production streaming pipelines, ideally with Kafka.

• Strong command of real-time event correctness, including ordering and sequencing, duplicate and gap detection, offsets and checkpoints, restart recovery, replay and backfill, idempotency, backpressure, reconciliation, and data validation.

• Strong SQL skills and production experience with a time-series or analytical database such as ClickHouse, QuestDB, or InfluxDB, including data modeling, partitioning, retention design, and query-performance tuning at scale.

• Strong distributed-systems fundamentals, with depth in one or more of the following: data APIs, routing and service discovery, high availability and failover, failure recovery, authorization, or backward-compatible data and client contracts.

• An ownership and operational mindset, with a strong focus on correctness, monitoring, reconciliation, data quality, backfills, incident response, and documentation.

• Comfortable participating in an on-call rotation and owning the investigation, mitigation, and prevention of production incidents.

• Experience maintaining or safely migrating a legacy production data system while keeping critical services available.

• Proactive use of AI tools in day-to-day engineering, with sound judgment around verification, security, and safety.

• Strong communication skills and fluency in English and Chinese.

Nice to Haves

• Experience building exchange REST/WebSocket connectors or feed handlers, particularly for order-book snapshot/delta streams, sequence and gap recovery, or exchange protocol changes.

• Knowledge of market microstructure, electronic trading, tick-data platforms, or market-by-order/market-by-price data models.

• Hands-on experience with ClickHouse or a comparable analytical database; Iceberg/Parquet or a comparable lakehouse; gRPC/Protobuf; Kubernetes; or service-discovery tools such as etcd. Expertise across every component is not expected.

• Experience developing data-access APIs or client libraries.

• Python experience for supporting tooling, analytics, and data operations.

• Experience with batch processing for historical data, reconciliation, backfills, or analytics.

• Exposure to AI/ML tooling or data products for model training and research.

• Interest in learning Rust for performance-critical components.

Perks & Benefits

• Competitive total compensation package.

• Learning and development programs and education subsidy for employees’ growth and development.

• Various team-building programs and company events.

• Wellness and meal allowances.

• Comprehensive healthcare schemes for employees and dependents.

• More that we would love to tell you about during the process.

Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong.