PySpark Backend Engineer – AI Security
2 weeks ago
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 PySpark Backend Engineer to join our expanding team dedicated to developing cutting-edge cybersecurity products from the ground up.
If you possess exceptional programming skills and have a passion for creating new applications or enhancing existing ones, we would love to meet you.
Responsibilities
- Design and implement backend logic using PySpark within Databricks, focusing on data processing using Spark Structured Streaming.
- Develop and maintain microservices and backend components in Python and C#, deployed in Kubernetes environments.
- Collaborate with product managers and backend teams to translate business requirements into Spark-based logic and services.
- Optimize Spark jobs for performance, reliability, and cost-efficiency in a cloud-native environment (Azure).
- Own features end-to-end: from refining requirements with product managers, through design and implementation, to deployment and support.
Requirements
- 5+ years of experience in backend development, with a strong focus on data-intensive applications.
- Hands-on experience with PySpark and Spark Structured Streaming in production environments – must
- Solid understanding of Spark internals, job optimization, and streaming semantics.
- Proficiency in Python. Experience with C# is an advantage.
- Experience building and deploying microservices in Docker/Kubernetes environments. Familiarity with cloud platforms (Azure/AWS/GCP)
- Experience working in Databricks
- Experience in cybersecurity or real-time data processing domains - advantage.
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