Cloud Data Engineer

• Collaborate with finance and actuarial teams to identify business challenges, propose, and develop cloud-based architectures and solutions.
• Analyze end-to-end business processes and implement automation using cutting-edge technologies.
• Design and build scalable data platforms, automated data ingestion, and integration pipelines.
• Utilize data management tools for data ingestion, quality, security, lineage, cataloging, and master data management.
• Work with data storage solutions, including Data Lakes, Relational Databases, and NoSQL Databases.
• Diagnose and resolve complex operational issues in enterprise environments, interacting with AWS cloud services, on-premises infrastructure, and external applications.

• Bachelor's degree or equivalent in Computer Science, Computer Engineering, Statistics, or related fields.
• Experience managing large-scale infrastructure across cloud platforms.
• Proficiency in data management architectures, such as data warehouses, data lakes, or data hubs.
• Hands-on experience (2+ years) in data engineering, handling structured and unstructured data from diverse sources.
• Expertise in implementing ETL, Data Streaming, or Data Analytics solutions (e.g., PySpark, Kafka).
• Strong knowledge of AWS Cloud platform features and capabilities.
• Experience working in Agile project environments.
• Familiarity with CI/CD or DevOps practices.
• Excellent written and verbal communication skills in English and Chinese.
• Passionate about learning and adopting new technologies.
• Thrives in a fast-paced, collaborative environment within a small, cross-functional team.
• Self-motivated and capable of independent task management.
• Strong interpersonal skills, with a preference for proven client interaction experience.

Morgan McKinley