Hong Kong Exchanges and Clearing Limited

AVP - System Development Manager - Data Platform - LME

Hong Kong Exchanges and Clearing Limited
Apply
1 month ago
Shenzhen, ChinaStaff+

Responsibilities

  • Design, build, operate, and continuously improve major streaming, batch, storage, or serving components of the data platform.
  • Operate Kafka clusters, including broker tuning, partition rebalancing, monitoring, disaster recovery, schema registry, and Kafka Connect.
  • Build and optimize Spark batch jobs and Flink or Spark Structured Streaming pipelines and frameworks.
  • Manage Iceberg tables and operate MinIO storage at scale, including compaction, snapshot expiration, lifecycle rules, tiering, and performance tuning.
  • Deploy and operate Trino, StarRocks, and ClickHouse clusters, including connector configuration, resource management, sharding, replication, materialized views, and query monitoring.
  • Build and maintain Airflow or Dagster DAGs and extend custom operators and sensors.
  • Implement platform-wide monitoring, dashboards, and alerting with OpenTelemetry, Prometheus, Grafana, and Loki.
  • Manage Kubernetes operations, Helm charts, operators, resource quotas, node affinity, and pod disruption budgets.
  • Own ArgoCD application sets, Helm-based deployments, and GitOps promotion pipelines from development to production.
  • Participate in on-call rotations and write post-mortems and runbooks.
  • Mentor mid-level engineers through pairing, design discussions, and code reviews.

Requirements

  • 6+ years of experience in data engineering, platform engineering, or backend infrastructure.
  • Strong Kubernetes experience, including Helm chart authoring, RBAC, network policies, persistent storage, and operators.
  • Solid Kafka experience covering topic design, consumer groups, offsets, lag monitoring, Kafka Connect, and schema registries such as Apicurio or Confluent.
  • Solid Spark experience with the DataFrame/Dataset API, Spark SQL, performance tuning, and production troubleshooting.
  • Working knowledge of Flink or Spark Structured Streaming for real-time pipelines.
  • Practical Iceberg experience with table maintenance, time travel, and catalog integration.
  • Hands-on Trino or Presto experience with connector configuration, query tuning, and resource groups.
  • Experience with an OLAP engine such as StarRocks, ClickHouse, or Doris, including table design, ingestion pipelines, and query optimization.
  • Proficiency in Python and either Scala or Java.
  • Experience with CI/CD and GitOps using ArgoCD or Flux, Helm, and Docker.
  • Experience with Airflow or Dagster for pipeline orchestration.
  • Preferred experience with OpenShift SCC, Routes, ImageStreams, and BuildConfigs; dbt; Great Expectations, Soda, or Deequ; Kafka Streams or ksqlDB; and DataHub or Atlas.

Benefits

  • Permanent employment with a standard 40-hour scheduled workweek.
  • Location: Shenzhen, China.
  • Participation in an on-call rotation is required.

Tech Stack

Apache AirflowApache FlinkApache KafkaApache SparkClickHousedbtDockerGrafanaHelmJavaKubernetesOpenShiftPrestoPrometheusPythonScala

Categories

Data EngineeringDevOps
Contact me