Data Engineer (Azure, Spark, Python)

About the Position

We are seeking a Data Engineer (Azure) to build and run scalable data pipelines and platforms on Microsoft Azure. You will work hands-on with Azure Data Factory, Azure Databricks, and Azure SQL, plus streaming, automation, and governance, to deliver reliable data products teams can trust.

Responsibilities

• Design and build batch and streaming data pipelines using Azure Data Factory and Azure Databricks
• Develop and optimize data models and workloads in Azure SQL and cloud data stores
• Implement event-driven data processing with Azure Event Hubs and Kafka
• Automate deployments using Azure DevOps pipelines and Infrastructure as Code
• Containerize services with Docker and run workloads on Azure Kubernetes Service (AKS)
• Implement data governance and lineage with Microsoft Purview
• Monitor platform health, costs, and performance using Azure Monitor and logging
• Partner with engineering and product teams to deliver end-to-end data solutions

Requirements

• Proven experience building data pipelines with Azure Data Factory
• Hands-on experience with Azure Databricks for data processing and orchestration
• Strong skills in Azure SQL plus Python and SQL for transformation and automation
• Knowledge of streaming patterns using Azure Event Hubs and/or Kafka
• Experience with Azure Data Lake Storage and Azure Cosmos DB in modern data platforms
• Familiarity with Azure DevOps and Infrastructure as Code (Bicep, Terraform, or Azure Resource Manager templates)
• Ability to apply governance and monitoring using Microsoft Purview and Azure Monitor
• Clear communication and collaborative problem-solving in cross-functional teams

Nice to Have

• Azure certifications related to data engineering or solution architecture
• Experience with big data architectures and advanced analytics
• Comfort working in agile delivery models and enterprise environments

Locations

• Suzhou, China
• 4 other locations

Language

• English