Backend Developer (Python, Go)

Summary

Data has never been more valuable and vulnerable. As cybercriminals become more sophisticated and regulations more strict, organizations struggle to answer one key question: “Is my data safe?

At Varonis, we see the world of cybersecurity differently. Instead of chasing threats, we believe the most practical approach is protecting data from the inside out. We’ve built the industry’s first fully autonomous Data Security Platform to help our customers dramatically reduce risk with minimal human effort.

At Varonis, we move fast. We’re an ultra-collaborative company with brilliant people who care deeply about the details. Together, we’re solving interesting and complex puzzles to keep the world’s data safe.

We work in a flexible, hybrid model, so you can choose the home-office balance that works best for you.

We are seeking a skilled Software Developer with a solid understanding of backend systems and a passion for working on data-driven projects. You will have the opportunity to design, implement, and maintain scalable services while also working with large datasets and contributing to data transformation tasks.

Responsibilities

• Develop, test, and maintain backend services and APIs with a focus on scalability, reliability, and performance.
• Work on data engineering tasks, such as processing and transforming large datasets to integrate into systems.
• Collaborate with cross-functional teams to design, implement, and maintain data systems and workflows.
• Contribute to the design and implementation of microservices and distributed systems.
• Participate in code reviews, writing unit tests, and maintaining high-quality code standards.
• Leverage Databricks for big data processing and analytics (experience with Databricks is a big plus).
  
  

• Strong experience with backend development and frameworks.
• Proficiency in Python (required) and knowledge of Go (preferred).
• Experience in data engineering, including working with large-scale data systems and data transformation.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and containerization (e.g., Docker, Kubernetes).
• Experience with Databricks or similar big data tools is highly advantageous.
• Knowledge and experience with machine learning projects is a plus.