Description:

Design, develop, and maintain robust data infrastructure for fraud detection and general data engineering.
Build scalable, high-performing data pipelines and storage systems.

Requirements:

3+ years of experience as a data engineer, preferably with fraud detection systems.
Proficiency in Python and SQL; knowledge of orchestration tools (e.g., Apache Airflow, DBT).
Strong database design and ETL/ELT workflow knowledge, including MySQL and ClickHouse.
Experience with production data pipelines and CI/CD processes.
Familiarity with data visualization platforms (e.g., Tableau, Superset).
Understanding of statistical techniques for fraud analysis.

Skills

Benefits