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Nexus Global Pty Limited

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Senior Data Engineer

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Summary

Senior Data Engineer in Hong Kong building and maintaining batch and streaming data pipelines, datasets, and data services end to end — from design and build through testing, deployment, and production support. Core stack includes Python/Java, advanced SQL, Spark, Airflow, Kafka, and cloud data platforms (Azure/AWS/GCP).

Role purpose: We're hiring a Senior Data Engineer to deliver high-quality data solutions across a range of business demands, building and maintaining pipelines, datasets, and data services that are reliable, secure, and easy to consume. This is a hands‑on engineering role.

Key responsibilities:

  • Build and maintain batch and/or streaming data pipelines end‑to‑end: ingest, transform, validate, and publish.
  • Develop reusable data transformation patterns and curated datasets for analytics and operational use cases.
  • Work from requirements through to production delivery: design, build, test, deploy, and support.
  • Implement data quality checks, reconciliations, and monitoring/alerting to keep data trustworthy.
  • Optimize performance and cost through query tuning, partitioning, and efficient computer usage.
  • Maintain clear documentation, data definitions, and runbook for supported pipelines.
  • Troubleshoot production issues, perform root cause analysis, and implement permanent fixes.
  • Collaborate with upstream/downstream teams to resolve data issues and improve interfaces/contracts.
  • Follow security and governance expectations for sensitive data, access controls, and audibility.
Requirements

Required skills and experience:

  • Minimum 8 years of strong hands‑on experience delivering data engineering solutions.
  • Strong programming skills in Python and/or Java, experience with advanced SQL, and solid data modelling skills.
  • Experience with distributed processing, e.g. Spark, and orchestration, e.g. Airflow or equivalent.
  • Experience with streaming/event platforms, e.g. Kafka/PubSub, is beneficial; ability to learn quickly if not.
  • Strong engineering discipline: Git, code reviews, automated testing, CI/CD, and observability.
  • Experience working with cloud data platforms: Azure/AWS/GCP and lake/lake‑house/warehouse patterns.
  • Proven ability to manage multiple data requests and priorities effectively and deliver at pace.

Skills

See also

Data Engineering jobs by country — openings, pay and top skills →

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