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
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