Cloud Data Engineer (Azure, Databricks)

Our client is now looking for talents to join their team:

Goal of the Project:

l   Implement a scalable cloud-based data platform to enable sustainable, reusable, secure, efficient ingestion, transformation, and storage of enterprise data across multiple sources.

l   Improve data consistency, reliability and controlled accessibility by automating ETL/ELT workflows, enforcing data quality checks, and reducing manual intervention by 30–40%.

l   Knowledge and experience of near real-time analytics capabilities to support business intelligence, predictive modeling, and faster decision-making for strategic initiatives.

Primary Responsibilities:

l   Optimize, operate at scale and enhance cloud-based data platform on Microsoft Azure (incl DataBricks)

l   Involve in cloud data platform enhancement project lifecycle with external vendor including design, development, testing, deployment, and documentation.

l   Work with Data Analyst to perform data preparation, cleansing, build optimized data models and visualization in Power BI

l   Perform proof of concept for cloud data products

Secondary Responsibilities:

l   Validate data workflows and integration points through rigorous testing (e.g., pipeline validation, schema checks, and performance benchmarking) to ensure solutions meet business and technical requirements.

l   Create operational playbooks and automation scripts to streamline deployment, monitoring, and troubleshooting, enabling efficient handover and long-term maintainability of data solutions.

l   Document data pipeline architecture, deployment processes, and operational runbooks to support effective troubleshooting and post-go-live maintenance by internal teams

Requirements:

• HD/Degree Holder. Related Certification in Azure Data platform/ Databricks is a must
• 3 years of professional experience related to data platform, especially familiar with data engineer side, and Strong on Python, Azure DataBricks, Azure Data Factory, Spark, ETL
• At least 2 years of work experience familiar with Databricks, including hands-on involvement in production implementation and Databricks Partitioning is a must
• Strong on speak and listen English & Cantonese
• Experience in software development lifecycle (SDLC).
• Understanding of data lifecycle and governance principles (e.g., data quality, lineage, security, and compliance).