Mid‑Level Data Engineer

We are looking for a Mid-Level Data Engineer to build and scale the Azure cloud data platform that powers enterprise-wide finance and supply chain analytics for a leading organisation.

You will join a central data team responsible for designing, implementing, and operating a Databricks‑based analytics platform on Azure. The role focuses on delivering robust data pipelines, high-quality datasets, and strong governance across multiple business units.

Responsibilities:
• Design, build, and maintain batch and incremental data pipelines using Azure Databricks and Azure Data Factory to ingest data from ERP and operational systems into Azure Data Lake Storage Gen2.
• Perform data preparation, cleansing, build optimized data models, and visualization in Power BI to support BI, finance, and operations analytics.
• Implement data quality checks, monitoring, and alerting to ensure accuracy, completeness, and timeliness of critical datasets.
• Collaborate closely with finance, supply chain, IT, and other stakeholders to translate business requirements into efficient, reliable data solutions.
• Contribute to data governance, including metadata management, lineage, and access control in coordination with the data platform and security teams.

Requirements:
• 3-5 years+ of hands‑on data engineering experience in cloud environments, preferably on Azure.
• Strong proficiency in PySpark and SQL, including performance tuning on large datasets.
• Willing to learn and experience with Azure Databricks, Azure Data Factory, and Azure Data Lake Storage Gen2 (or equivalent tools on other clouds).
• Good understanding of modern data warehousing or lakehouse architectures, dimensional modelling, and ELT/ETL best practices.
• Experience building and operating production‑grade data pipelines, including testing, monitoring, and incident handling.
• Excellent communication skills in English and Cantonese.