Data Engineer

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.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines to integrate data from diverse sources, optimizing for performance and cost efficiency.
• Leverage Databricks and other modern data platforms to manage, transform, and process data
• Collaborate with data scientists and other software teams to understand data needs and ensure data solutions meet business requirements.
• Optimize data processing workflows for performance and scalability.
  
  

• 3+ years of experience in data engineering, including cloud-based data solutions.
• Proven expertise in implementing large-scale data solutions.
• Proficiency in Python, SQL, PySpark is a plus.
• Experience with ETL processes.
• Experience with cloud and technologies such as Databricks (Apache Spark) and Azure Data factory.
• Strong analytical and problem-solving skills, with the ability to evaluate and interpret complex data.
• Experience leading and designing data solutions end-to-end, integrating with multiple teams, and driving tasks to completion.
  
  

• Familiarity with either On-premise or Cloud storage systems
• Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team.