Were looking for a Senior Software Engineer to join 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 worlds largest enterprises.
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 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
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 worlds largest enterprises.
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 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
Requirements:
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:
Backend development (Java, Spring Boot)
Streaming systems (Kafka or similar)
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
Advantages:
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
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:
Backend development (Java, Spring Boot)
Streaming systems (Kafka or similar)
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
Advantages:
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
This position is open to all candidates.
