Sr. Software Engineer

Responsibilities

• Design and build Cribl’s customer-facing metric store for high-volume telemetry data.
• Write clean, maintainable, and testable code with focus on performance, observability, and operational resilience.
• Build scalable backend services and APIs for metric ingestion, storage, metadata management, and query execution.
• Work on data modeling and storage patterns for time-series data, including high-cardinality dimensions, labels, fingerprints, rollups, and retention strategies.
• Partner with Product and Design to turn complex observability workflows into intuitive customer-facing capabilities.
• Collaborate with engineers to integrate metric storage and query capabilities into broader product experiences.
• Analyze and improve query performance, ingestion throughput, storage efficiency, and system reliability.
• Define engineering practices for a new product area, including testing, deployment, monitoring, and operational readiness.
• Coach and empower less senior engineers.
• Plan and forecast quarterly goals balancing new features, technical debt, reliability, and customer needs.
• Champion the full software development lifecycle from requirements through production support.
• Share on-call responsibilities.

Requirements

• Ability to comply with U.S. government security requirements for access to FedRAMP-authorized systems (may include U.S. citizenship).
• Strong experience building backend services in complex, large-scale distributed systems.
• Ability to write clean, maintainable, and testable production code, preferably in Node.js and TypeScript.
• Experience building SaaS platforms, data platforms, observability systems, or high-volume cloud services.
• Experience working with time-series data, metrics, telemetry pipelines, query systems, or analytical databases.
• Experience designing APIs and interfaces that are secure, intuitive, and built for long-term evolution.
• Strong understanding of data structures, algorithms, Linux, networking, and distributed systems fundamentals.
• Experience with cloud infrastructure on AWS or another major cloud provider.
• Experience with storage systems, query performance, indexing strategies, partitioning, caching, or data lifecycle management.
• Self-starter who can operate with minimal supervision and learn quickly in ambiguous technical areas.
• Dedicated to elegant, high-quality software.
• Comfortable making tradeoffs between correctness, performance, cost, operability, and customer experience.

Nice-to-Haves

• Experience with observability concepts such as metrics, labels, dimensions, cardinality, histograms, counters, gauges, and query languages such as PromQL.
• Experience with systems such as ClickHouse, Prometheus, Mimir, Thanos, VictoriaMetrics, OpenTelemetry, Kafka, Kinesis, S3, or similar.
• Experience using testing frameworks such as Mocha, Jest, Cypress.
• Experience with CI/CD pipelines such as Bitbucket, Jenkins, CircleCI, GitHub Actions.