Senior Real-Time Market & Trading Data Engineer

OKX

Hong Kong

On-site

HKD 900,000 - 1,500,000

Full time

14 days+

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Benefits offered by this job

Competitive total compensation package

Learning and development programs and

Wellness and meal allowances

Comprehensive healthcare schemes for员工

Job summary

OKX in Hong Kong is seeking a hands-on Senior Market & Trading Data Engineer (Java) to build and operate our core data platform for public market data and proprietary trading data. You will own ingestion, normalization, and delivery pipelines from exchanges and internal sources, ensuring correctness, latency, and reliability.

The role emphasizes strong Java performance tuning, real-time streaming with Kafka, and scalable storage with Iceberg/ClickHouse.

Qualifications

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, 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.

Responsibilities

Build and operate high-throughput Java pipelines for public market data, including trades, 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 Chronicle Queue, Kafka, relational and time-series databases, 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 on-call rotation and 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 migrations toward Kafka, ClickHouse, Iceberg, and Kubernetes through parallel runs, reconciliation, and controlled cutovers.
Use AI assistants and LLM tooling responsibly to accelerate development, debugging, and data operations, and help the team adopt effective AI-native workflows.