Senior Data Engineer (Cybersecurity)

• Maintain and enhance existing data processes with a focus on reliability, scalability, and performance optimization
• You will become a core member of a small, highly proactive engineering team working on a large-scale cybersecurity product.

About Sigma Software

Join a high-impact cybersecurity project focused on protecting applications from automated attacks and malicious activity.

We are looking for a Senior Data Engineer who thrives in autonomous environments, enjoys solving complex data challenges, and is ready to drive modernization initiatives across scalable data systems.

As part of Sigma Software, you will collaborate with experienced international teams and have the opportunity to shape scalable data infrastructure used in cybersecurity products operating at scale.

We value ownership, strategic thinking, and technical excellence, offering an environment where engineers can influence architectural decisions, drive meaningful improvements, and continue growing professionally.

CUSTOMER Our Customer is a global cybersecurity company delivering advanced digital protection solutions for businesses, organizations, and communities worldwide.

Operating across multiple cybersecurity domains, the company focuses on identifying vulnerabilities, preventing threats, and strengthening digital resilience through scalable and reliable security products.

PROJECT The project focuses on developing and improving a cybersecurity solution designed to protect applications from automated attacks and malicious traffic.

The team works on scalable, high-performance data infrastructure powering security analytics, monitoring, and detection capabilities.

Responsibilities

• Analyze and deeply understand existing data models, workflows, tables, and processing jobs
• Identify technical gaps, bottlenecks, inefficiencies, and opportunities for architectural improvements
• Design, optimize, and support large-scale data pipelines and transformation processes
• Drive modernization initiatives across the data platform and contribute to long-term architectural evolution
• Optimize complex SQL queries and improve data processing latency and efficiency
• Collaborate with product engineering and cross-functional teams on technical solutions and implementation strategies
• Contribute to both short-term delivery goals and long-term platform development initiatives
• Ensure adherence to best practices in data engineering, system reliability, and performance optimization
• Participate in technical discussions, solution design, and continuous improvement initiatives
• 5+ years of commercial experience in Data Engineering Expert-level Python skills Expert-level SQL skills with practical experience optimizing complex queries for performance and scalability
• The role requires deep involvement in understanding existing systems, including legacy code and interconnected services, identifying inefficiencies and technical gaps, and driving meaningful improvements across the platform.
• You will collaborate closely with product engineering teams, influence technical decisions, and contribute to both immediate optimizations and long-term platform evolution.

Requirements

• Strong hands-on experience with DBT for data transformation and modeling
• Solid understanding of database concepts, including DDL, DML, indexing, normalization, and advanced SQL techniques Hands-on experience working with Snowflake Experience with Elastic Stack technologies
• Proven experience designing, building, and maintaining large-scale data pipelines

Strong analytical thinking and problem-solving skills

• Ability to work independently in a high-autonomy engineering environment
• Experience driving technical initiatives from idea through implementation
• Strong communication and collaboration skills Upper-Intermediate English level or higher WILL BE A PLUS Experience with Airflow for workflow orchestration
• The environment combines modernization of legacy systems with the development of reliable and scalable data workflows, requiring strong ownership and close collaboration with cross-functional engineering teams.
• Snowflake, DBT, SQL, Python, Elastic Stack, Airflow