Senior Data Infrastructure Engineer

About the company:

Cybereason is seeking a passionate and skilled Information Security Engineer to join our team. In this role, you’ll be responsible for enhancing the security of our enterprise environment, working with a variety of security tools and technologies. We're looking for individuals with a strong background in information security who are eager to help shape the future of cybersecurity and protect our organization from evolving threats.

About the Role:

• Cybereason is seeking a Senior Data Infrastructure Engineer to architect and scale the data backbone that powers our cutting-edge cybersecurity analytics. In this role, you’ll build distributed systems that process billions of security events daily, powering our platform with real-time and historical threat intelligence. You’ll work at the intersection of big data, cloud-native engineering, and cybersecurity, ensuring our infrastructure can support advanced analytics and machine learning at scale.
• Key Responsibilities:
• Design and develop petabyte-scale data infrastructure and real-time streaming systems capable of processing billions of events daily
• Build and optimize high-throughput, low-latency data pipelines for security telemetry
• Architect distributed systems using cloud-native technologies and microservices patterns
• Design and maintain data lakes, time-series databases, and analytical stores optimized for security use cases
• Implement robust data governance, quality, and monitoring frameworks across all data flows
• Continuously optimize for performance, scalability, and cost-efficiency in large-scale data workloads
• Collaborate with data science and security teams to enable advanced analytics and ML capabilities
• Ensure data infrastructure complies with strict security, availability, and compliance requirements
• Required Qualifications:
• Bachelor’s degree in Computer Science, Engineering, or related field
• 7+ years of experience building and maintaining large-scale data infrastructure
• Proven experience operating petabyte-scale systems processing billions of records per day
• Expert-level proficiency with stream processing: Apache Flink, Kafka, Pulsar, Redpanda, Kinesis
• Deep experience with analytical and time-series databases: ClickHouse, Druid, InfluxDB, TimescaleDB
• Familiarity with distributed storage: Hadoop (HDFS), Amazon S3, GCS, Azure Data Lake
• Strong skills in: Rust, Go, Scala, Java, or Python for high-performance systems
• Cloud expertise: AWS (EMR, Redshift, Kinesis), GCP (Dataflow, BigQuery, Pub/Sub), or Azure equivalents
• Solid experience with Kubernetes, Docker, and Helm; familiar with service mesh like Istio or Linkerd
• Strong grasp of data lake/lakehouse architectures and modern data stack tools
• Preferred Qualifications:
• Experience with Apache Iceberg, Delta Lake, or Apache Hudi
• Familiarity with Airflow, Prefect, or Dagster for orchestration
• Knowledge of search platforms: Elasticsearch, OpenSearch, or Solr
• Experience with NoSQL: Cassandra, ScyllaDB, or DynamoDB
• Familiar with columnar formats: Parquet, ORC, Avro, Arrow
• Experience with observability stacks: Prometheus, Grafana, Jaeger, OpenTelemetry
• Familiar with Terraform, Pulumi, or CloudFormation for IaC
• GitOps tools: ArgoCD, Flux for automated deployments
• Exposure to data mesh, data governance, and metadata tooling (Apache Atlas, Ranger, DataHub)
• Background in cybersecurity, SIEM, or security analytics platforms
• Familiarity with ML infrastructure and MLOps best practices
• Technical Skills and Knowledge:
• Stream Processing: Real-time analytics, windowing, state management, exactly-once semantics
• Distributed Systems: Partitioning, consistency, HA, failover, load balancing
• Data Lakes & Lakehouses: Multi-zone design, schema evolution, metadata management
• Cloud-Native Patterns: Microservices, event-driven design, auto-scaling, regional failover
• Performance Tuning: Query optimization, resource allocation, caching, compression
• Governance: Lineage tracking, anomaly detection, quality controls, regulatory compliance
• Security: Encryption, zero-trust principles, access control, audit logs
• Observability: Metrics, logs, distributed tracing, alerting
• Key Competencies:
• Proven track record of building and scaling high-volume, high-throughput data systems
• Strong analytical and problem-solving skills in complex distributed environments
• Excellent communication and collaboration across cross-functional teams
• Self-driven with ability to manage multiple high-impact infrastructure initiatives
• Passionate about data architecture and staying ahead of emerging tech
• Experience mentoring engineers and shaping technical direction
• What We Offer:
• Work on cutting-edge cybersecurity technology
• Collaborative and innovative environment
• Continuous learning opportunities
• Competitive salary and benefits

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