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