AZURE DATABRICKS DATA ENGINEER, LISTED FIRM

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Our client is a well-known listed public transport company in Hong Kong. Our client is seeking a highly skilled Data Engineer to design, implement, and optimize the cloud-based data platform on Microsoft Azure. The role focuses on building scalable, reliable, and secure data pipelines that enable seamless analytics, business intelligence, and data-driven decision-making across the enterprise.

 

Responsibilities:

• Design, develop, and enhance ETL/ELT workflows to manage structured and unstructured data from multiple sources within an Azure environment.
• Build and maintain scalable data pipelines using Azure Data Factory and Databricks, ensuring high availability, performance, and data integrity.
• Collaborate with cross-functional teams, including data analysts and architects, to support data modeling, transformation, and visualization using tools such as Power BI.
• Implement effective data quality checks, validation scripts, and performance benchmarking to ensure trusted and timely delivery of business-critical data.
• Develop automation scripts and operational playbooks for deployment, monitoring, and troubleshooting, ensuring efficient platform maintenance and knowledge transfer.
• Participate in full project lifecycles — including design, development, testing, and documentation — in coordination with internal teams and external vendors.
• Conduct proofs of concept (POCs) for new cloud data solutions to evaluate emerging tools, frameworks, and architecture improvements.

Requirements:

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related discipline.
• Minimum of 2–4 years of experience in data engineering or related roles, preferably within a cloud-native environment.
• Proficiency in Azure Data Factory, Databricks, and Power BI for data pipeline orchestration and analytics delivery.
• Strong programming and scripting skills in Python and SQL, with experience implementing automation in data workflows.
• Hands-on experience with data modeling, data quality management, and performance optimization.
• Familiarity with real-time analytics capabilities and data warehousing principles.
• Excellent problem-solving, communication, and documentation skills with a proactive mindset for continuous improvement.