Lead Data Engineer, Zalo

• Design and develop the Feature Store to support efficient data processing, analysis, and storage;

• Build and enhance the Rule Engine to facilitate real-time monitoring and rapid response to emerging clone/spam patterns on Zalo;

• Improve system workflows to minimize manual oversight and enhance overall efficiency;

• Directly analyze and monitor patterns of “bad” activities on Zalo. Make informed decisions and establish rules for swift mitigation within a 1-24 hour timeframe;

• Develop and implement scoring and classification models to identify malicious users/groups;

• Create meaningful and insightful reports to help guide data-driven decision-making to identify patterns of fraud, spam, and further provide actionable insights.

👾 What you will need

• 5+ years of hands-on experience in data engineering, focusing on real-time and batch processing systems;

• Coding & Automation Skills – Proficiency in Python, Bash shell or Java to develop custom security detections;

• Data Analyst Skills - Experience in writing advanced SQL queries. Ability in manipulate and extract insights from large, column-based raw data. Ability to analyze complex datasets to identify valuable insights, detect anomalies, and predict potential malicious actors or activities;

• Problem-Solver Mentality – A passion for hunting down new threats, identifying gaps, and proposing solutions;

• Strong written and verbal communication & Leadership – Ability to mentor, collaborate, and communicate technical concepts effectively.

Preferred Qualifications:

• Proficiency in Rust, familiar with ELK stack, Redis or similar technologies 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.