Data Application Engineer

About Hytech

Hytech is a leading fintech company, pioneering innovative financial technology solutions that empower clients to manage their finances with unmatched efficiency, security, and convenience. As a trailblazer in the fintech industry, we are committed to driving digital transformation and redefining the future of finance through our cutting-edge platforms and applications.

About the Role

Key Responsibilities

• Develop and continuously iterate the data platform
• Build and maintain data pipelines for user behavior data processing based on Flink, ensuring the completeness, accuracy, and stability of tracking data.
• Design and maintain the user tagging system, including tag generation, quality validation, and tag governance.
• Build and maintain data application pipelines to support downstream data needs from product, operations, analytics, and algorithm teams, including behavior and user tag data.
• Collaborate closely with product managers, data analysts, and business teams to drive the application of user data in refined operations and product optimization.
• Continuously improve the performance, observability, maintainability, and scalability of the data application pipeline.

Qualifications

• Bachelor's degree or above in Computer Science, Software Engineering, Data Science, or related fields. At least 5 years of experience in complex system development.
• Proficient in Java, Python, and SQL for data application development or data processing.
• Familiar with the Apache Flink framework and experienced in real-time or near real-time processing of user behavior data.
• Solid understanding of event tracking systems, including event definitions, attributes, user ID mapping, and tracking data flow.
• Familiar with common user tag categories (e.g., behavioral tags, attribute tags, statistical tags) and their production mechanisms.
• Experience with relational databases (RDBMS), NoSQL databases, and analytical data systems (OLAP), such as MySQL, Redis, HBase, Doris, and ClickHouse.
• Strong problem-solving and troubleshooting skills, with the ability to translate business requirements into data processing solutions and collaborate effectively across teams.