PCA Data Engineer

Responsibilities

• Design, develop, and maintain robust data pipelines and ETL processes using tools like Azure Data Factory and Python across internal and external systems.
• Translate business requirements into technical requirements.
• Create and maintain technical documentation related to data architecture, integration flows, and processes.
• Monitor and troubleshoot pipeline performance and reliability with minimal oversight.
• Collaborate with other engineers, delivery leads and platform teams to ensure data solutions meet business needs while following best practices.
• Proactively manage data quality, error handling, monitoring, and alerting to ensure timely and trustworthy data delivery.
• Perform debugging, application issue resolution, root cause analysis, and assist in proactive/preventive maintenance.
• Participate in the code review, performance tuning and continuous improvements efforts.
• Collaborate with data analysts, business users, and developers to ensure the accuracy and efficiency of data solutions.
• Work with the extended data team to define, develop, and maintain shared data models and definitions.

Qualifications

• A minimum of 3 years of experience as a Data Engineer, working with cloud platforms (Azure, AWS).
• Strong hands-on expertise in Azure Data Factory, Azure Data Lake, Python, and SQL.
• Familiarity with cloud storage (Azure, AWS S3) and integration techniques (APIs, webhooks, REST).
• Experience with modern data platforms like Snowflake and Microsoft Fabric.
• Solid understanding of Data Modeling, pipeline orchestration and performance optimization.
• Strong problem-solving skills and ability to troubleshoot complex data issues.
• Excellent communication skills, with the ability to work collaboratively in a team environment and support business stakeholders.
• Familiarity with tools like Power BI for data visualization is a plus.
• Experience working with or coordinating with overseas teams is a strong plus.