Senior Data Engineer
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.
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.