Site Reliability Engineer, Data & Observability Platform


Hong Kong

Target profile

You will love this job if:

  • You are pioneering and innovative and want to be part of the cutting-edge and disruptive crypto-currency world
  • You are eager to learn new knowledge in both financial and technical fields
  • You thrive in a non-hierarchical organization with a casual working environment
  • You enjoy solving complex distributed systems challenges and optimizing streaming data pipelines
  • You value comprehensive documentation and collaborative problem-solving

Team / Role

As an Engineer, you will:

SRE & Observability:

  • Own the observability of the platform end to end: decide what to measure, instrument it, collect it, store it, and put it in front of people
  • Build Grafana dashboards and alerts that name what broke and what to check next — not alerts that merely report a number crossing a line
  • Run the production systems: diagnose silent failures, recover missed data, and fix the cause so it doesn’t recur
  • Ship changes through CI/CD and GitOps, and know the difference between “merged” and “live”
  • Operate streaming workloads on Kubernetes (EKS) — resource budgeting, config delivery, capacity, and why an OOM-kill can also be a data-loss event
  • Provision the AWS resources behind the platform as code (we use Terraform; we’ll show you ours)
  • Participate in on-call for the data and observability platform

Data Pipeline Engineering:

  • Build and maintain the near-realtime pipelines that carry telemetry and logs from source to quarriable table
  • Reason about delivery guarantees (at-most-once vs at-least-once) and what they mean for the numbers on a dashboard
  • Design data quality checks — route bad records for investigation rather than dropping them silently
  • Design and optimize OLAP tables so billion-row queries return fast: sort keys, partitioning, deduplication, retention
  • Write and tune the SQL behind dashboards and analytics
  • Translate a request like “show me p99 latency per venue” into a pipeline change and a table design

Required skillset

You should get in touch if:

  • University degree in Computer Science, Software Engineering or related disciplines
  • At least 4-7 years relevant working experience
  • Observability and monitoring in production — instrumenting services, building dashboards, writing alerts that are worth acting on, and diagnosing a live incident from metrics and logs together (Prometheus, Grafana, Loki, ELK, Datadog, CloudWatch — any equivalent stack)
  • CI/CD — delivering your own changes through a pipeline (GitLab CI, Jenkins, GitHub Actions, or similar), not handing them to someone else
  • A distributed stream processing engine in production (Flink, Spark Structured Streaming, or similar)
  • An OLAP / columnar database — designing tables and tuning queries, not just reading from them (ClickHouse, BigQuery, Druid, Redshift, or similar)
  • Kubernetes working knowledge — deployments, resource requests and limits, config delivery, reading pod state
  • Strong programming in at least one of Python, Scala, Java or Rust, plus fluent analytical SQL
  • Ability to troubleshoot production systems methodically, and the instinct to fix the cause rather than the symptom

It is a plus if:

  • OpenTelemetry, distributed tracing, or high-cardinality telemetry at scale
  • Airflow (DAGs, scheduling, task orchestration)
  • Infrastructure as code beyond the basics (Terraform modules, drift, targeted applies)
  • Build tools for JVM or multi-module projects (Maven, Gradle, sbt, Cargo)
  • Familiarity with message queues (SQS, Kafka, or similar) and event-driven architec

If you are interested, submit your application now.

 

Apply now