Zalo

What you will do Design, develop, maintain, and optimize ETL pipelines for real-time and batch data processing; Work with technologies such as Redis, Kafka, Python, ELK, and ScyllaDB to ensure efficient data processing; Improve the performance and reliability of existing data pipelines and processing jobs; Implement scalable real-time data processing systems using Redis, Kafka, and column-based databases; Create meaningful and insightful reports to help guide data-driven decision-making to identify patterns of fraud, user cloning, and spam, and further provide actionable insights; (For lead) Mentor engineers and contribute to setting best practices for data processing across the organization;

What you will need 3+ years of hands-on experience in data engineering, focusing on real-time and batch processing systems; Strong experience with Redis, Kafka, column-based databases, and real-time data streaming; Proficient in Python, Bash shell and familiar with ELK stack, ScyllaDB or similar technologies; Ability to create clear and actionable reports from complex datasets; Strong communication skills, with the ability to advocate for improvements and speak up when proposing better solutions; Self-motivated, detail-oriented, and results-driven with strong problem-solving skills; Preferred Qualifications:

Proficiency in Rust, gawk, and Java is a plus; Experience analyzing large datasets to detect anomalies, fraud, and suspicious behaviors is a big plus; Experience working in an on-prem environment.