Cloud Data Engineer (Azure, Databricks)
Salary: $30,000 – $45,000 per month
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).