Data Platform Engineer/ Data Engineer

Venturenix Limited; Hong Kong; On-site; HKD 480,000 - 720,000; Full time

Job summary

Venturenix Limited seeks a data engineering/DevOps professional to design and maintain scalable data ingestion and processing pipelines using Apache Airflow in a HK-based environment. You will manage Data Lake architectures, deploy containerized workloads on Kubernetes, and implement CI/CD practices to ensure high availability and data integrity.

The role requires hands-on experience with Airflow, Data Lakes, Kubernetes, Docker, and DevOps tools, plus strong Python/SQL/Shell scripting and

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
• 2 to 4 years of hands‑on experience in data engineering, data platform engineering, or DevOps roles.
• Strong, hands‑on expertise with Apache Airflow for workflow orchestration and pipeline management.
• Proven experience managing and optimizing Data Lake architectures.
• Working knowledge of Kubernetes and containerization technologies (Docker).
• Practical experience with DevOps methodologies, CI/CD tools, and automated deployment pipelines.
• Proficiency in Python, SQL, and Shell scripting for system automation and data processing.
• Good communication, problem‑solving, and analytical skills.

Responsibilities

• Design, construct, and maintain scalable data ingestion and processing workflows using Apache Airflow.
• Manage, optimize, and expand enterprise Data Lake infrastructure to ensure high availability, performance, and data integrity.
• Maintain and deploy containerized data services and pipeline workloads on Kubernetes clusters.
• Integrate DevOps best practices, automated CI/CD pipelines, and infrastructure management across data platforms.
• Monitor data pipeline health, troubleshoot production incidents, and perform root-cause analysis to ensure continuous operational uptime.
• Collaborate closely with data scientists, business analysts, and IT infrastructure teams to refine data integration capabilities.

Skills

Airflow

Data Lake

Kubernetes

Docker

DevOps

CI/CD

Python

SQL

Shell scripting

Communication

Problem solving

Analytical thinking

Education

Bachelor’s degree in CS/IT/SE

Tools

Airflow

Kubernetes

Docker

CI/CD

Job description

Design, construct, and maintain scalable data ingestion and processing workflows using Apache Airflow.

Manage, optimize, and expand enterprise Data Lake infrastructure to ensure high availability, performance, and data integrity.

Maintain and deploy containerized data services and pipeline workloads on Kubernetes clusters.

Integrate DevOps best practices, automated CI/CD pipelines, and infrastructure management across data platforms.

Monitor data pipeline health, troubleshoot production incidents, and perform root-cause analysis to ensure continuous operational uptime.

Collaborate closely with data scientists, business analysts, and IT infrastructure teams to refine data integration capabilities.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline.

2 to 4 years of hands‑on experience in data engineering, data platform engineering, or DevOps roles.

Strong, hands‑on expertise with Apache Airflow for workflow orchestration and pipeline management.

Proven experience managing and optimizing Data Lake architectures.

Working knowledge of Kubernetes and containerization technologies (Docker).

Practical experience with DevOps methodologies, CI/CD tools, and automated deployment pipelines.

Proficiency in Python, SQL, and Shell scripting for system automation and data processing.

Good communication, problem‑solving, and analytical skills.

Desirable Qualifications

Experience working within financial institutions, banking environments, or public sector bodies.

Exposure to cloud platforms (AWS, Azure, GCP) or hybrid cloud infrastructure.