Senior Java Backend Developer - Data Platform Group

At Thales, we know technology has the ability to make our world more secure, sustainable, and inclusive – and that it’s all driven by human intelligence.

Because it takes human intelligence to build and power the systems and solutions that people depend on every day. So we stay curious and make space for diverse points of view. We share what we know and we challenge what’s possible.

We’re driving progress in some of the world’s most important industries - from the bottom of the oceans to the depths of space and cyberspace - and from manufacturing to engineering, we work together to build a future we can all trust.

Imperva, a Thales company, is a globally recognized cybersecurity leader, dedicated to securing data and applications across diverse environments. Our cutting-edge solutions empower organizations to safeguard their most critical assets, ensuring robust protection against emerging threats.

Imperva, a Thales company, is a globally recognized cybersecurity leader dedicated to securing data and applications across diverse environments. Our cutting‑edge solutions help organizations protect their most critical assets against emerging threats.

Thales believes that technology becomes truly powerful when driven by human intelligence. We value curiosity, diverse perspectives, and bold thinking—and we are proud to be ranked among Israel’s Top 50 High‑Tech Companies to Work For in 2025 (Dun & Bradstreet) and offer a flexible hybrid work model from our Rehovot office.

We’re looking for a Senior Data Platform Engineer to join Imperva’s Data Infrastructure team, building the systems that power our Application Security platform at scale.

In this role, you will design and develop the data backbone that processes billions of security events daily, enabling real-time protection, analytics, and insights for the world’s largest enterprises.

Imperva develops cybersecurity solutions that protect critical applications, APIs, and data across cloud and hybrid environments. Our platform operates at massive scale, handling high-volume, low-latency data streams with strict reliability and performance requirements.

Fortune 500 companies rely on Imperva to secure their most asset - data.

Our stack includes AWS, Kubernetes, Kafka, Spark, RDS, OpenSearch, and Java/Spring Boot, alongside real-time components built with Go, C, and Linux.

About the Role:

As a Senior Platform Engineer on the Data Infrastructure team, you will build and evolve large-scale data systems that ingest, process, store, and serve security data across multiple products.

You will take ownership of core data services and pipelines, working on both real-time and batch processing systems. This includes improving scalability, optimizing performance, and ensuring high availability of critical data flows.

You are a hands-on engineer who enjoys solving complex data challenges and working with distributed systems at scale.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines (real-time and batch)
• Develop and optimize systems for high-throughput, low-latency data processing
• Work with streaming technologies (e.g., Kafka) and processing frameworks (e.g., Spark, Flink)
• Design and manage data storage solutions across relational, NoSQL, and search systems
• Improve data reliability, consistency, and observability across the platform
• Collaborate with product teams to enable data-driven features and analytics
• Troubleshoot and resolve complex production issues in distributed data systems
• Continuously improve system performance, scalability, and cost efficiency
• Contribute to architectural decisions within the data infrastructure domain
  
  

• 6+ years of experience as a backend, data, or platform engineer in a cloud-native environment
• Strong experience building distributed data systems and pipelines
• Hands-on experience with:
• Streaming systems (Kafka or similar)
• Backend development (Java, Spring Boot)
• Cloud platforms (AWS preferred)
• Solid understanding of distributed systems concepts (scalability, fault tolerance, data consistency)
• Experience with data storage technologies such as PostgreSQL/RDS, OpenSearch/Elasticsearch, or NoSQL systems
• Experience with Kubernetes and containerized environments
• Strong debugging and problem-solving skills in production systems
• Good communication skills and ability to collaborate across teams
  
  

• Experience with big data frameworks (Spark, Flink, Presto)
• Familiarity with workflow orchestration tools (Airflow or similar)
• Experience designing high-scale event-driven architectures
• Knowledge of data modeling and schema design for large-scale systems
• Experience with observability tools (logs, metrics, tracing)
• Exposure to MLOps or data pipelines supporting AI/ML systems
• Experience with multi-region deployments and large-scale cloud architectures