Data Engineer
1 week ago
Patsnap empowers IP and R&D teams by providing better answers, so they can make faster decisions with more confidence. Founded in 2007, Patsnap is the global leader in AI-powered IP and R&D intelligence. Our domain-specific LLM, trained on our extensive proprietary innovation data, coupled with Hiro, our AI assistant, delivers actionable insights that increase productivity for IP tasks by 75% and reduce R&D wastage by 25%.
Key Responsibilities
- Develop and maintain large-scale data processing systems, ensuring data security, stability, and availability;
- Analyze new data requirements, design data processing solutions, write relevant documentation, and implement code;
- Monitor data quality, design and implement targeted optimization solutions, and continuously improve data integrity and accuracy;
- Optimize data processing frameworks and performance, enhancing the efficiency of system data handling to support rapid iteration of product data;
- Collaborate with data architects, participate in architecture upgrades and updates, and enhance system scalability and stability.
Desired Qualifications
- Bachelor's degree or above in computer science, data engineering, software engineering, or related fields; at least 3 years of experience in data development;
- Proficiency in Java or Python with a solid programming foundation;
- Familiarity with basic components of big data processing, such as Flink and Spark, with experience in performance optimization preferred;
- Familiarity with Linux systems and common operations;
- Strong sense of responsibility and proactive learning ability, able to adapt flexibly in a fast-paced environment;
- Clear thinking with excellent communication skills and team spirit, able to collaborate effectively with team members from diverse cultural backgrounds;
- Basic understanding of data privacy and compliance, capable of working in a regulatory environment.
Why PatSnap
Technical Growth: Directly participate in large-scale data processing and optimization projects, gaining practical technical experience.
Systematic Training: Engage in architecture optimization under the guidance of senior data architects, enhancing data processing and system design capabilities.
Diverse Team: Rich opportunities for cross-departmental and multinational collaboration, helping you rapidly grow into a full-stack data engineer.
Career Development: Clear career development paths and ample space for growth.
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