The Сustomer provides comprehensive cybersecurity solutions designed to protect individuals, organizations, and communities. Operating across various sectors, the company addresses vulnerabilities and ensures protection against a wide range of risks, especially in the digital space.

The product is a solution to safeguard applications from automated attacks. 

 
The engineer is expected to operate as a core member of a small, high-autonomy, proactive team focused on: 

• developing a deep understanding of a core products including legacy code and multiple services; 

• proactively finding problems, inefficiencies, risks, technical gaps and areas for improvement, implementing them; 

• negotiating with product engineering teams to get buy-in for changes implementation; 

• planning short-term wins and long-term improvement strategy. 

Responsibilities: 
•  Maintain and enhance existing data processes, ensuring reliability, performance, and scalability; 
•  Build a full understanding of existing tables, flows, and jobs - what the data is, where it's used, where it can be improved, where to build new ones; 
•  Drive system reliability and performance improvements across all data workflows; 
•  Own and execute data process modernization initiatives; 
•  Collaborate cross-functionally to ensure architectural alignment and best-practice adoption. 

Must-Have Requirements: 
•  5+ years of overall experience in Data Engineering; 
•  Expert-level SQL skills: being able to optimize complex queries for latency and performance; 
•  Proficiency with DBT for data transformation and modeling; 
•  Strong data engineering fundamentals and database knowledge (DDL/DML/SQL); 
•  Hands-on experience with Snowflake and Elastic; 
•  Deep experience building, scaling, and managing large-scale data pipelines; 
•  Proven ability to work independently, take ownership, and drive initiatives to completion. 

 
Nice-to-Have: 
• Practical experience with Airflow for workflow orchestration.

Timezone: EU/Ukraine