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Salary: USD 225,250 - 265,000 / annual
Horizon3.ai is a fast-growing remote cybersecurity company building NodeZero, an autonomous penetration testing platform used by organizations from educational institutions to Global 100 enterprises. The platform delivers production-safe autonomous pentests and security assessments that scale across internal, external, cloud, and hybrid environments.
You will lead the Data Streaming sub-team within Data Ingestion, reporting to the Senior Manager of Data Ingestion. Data Streaming is responsible for reliably collecting, normalizing, and routing raw pentest telemetry data—every IP address, open port, credential, vulnerability finding, and asset relationship discovered by NodeZero flows through these pipelines before becoming actionable customer insights. This is a mission-critical function: pipeline stalls directly impact pentest result delivery.
Key responsibilities include:
- Lead and grow the Data Streaming sub-team from its current state to 6–7 engineers, owning engineering execution, team health, sprint cadence, technical design reviews, and code quality.
- Own SLOs for ingestion throughput, latency, and error rates; build on-call processes and runbooks to maintain production pipeline health.
- Maintain stable ingestion schemas and data contracts between NodeZero runners, Security Research, and Database Platform teams; carefully evolve contracts as new pentest capabilities ship.
- Scale ingestion pipelines to handle NodeZero's growth—more customers, larger environments, new data types—without proportional operational overhead.
- Partner cross-functionally with Security Research (data source), Database Platform (downstream consumer), and Asset Inventory teams to align on data quality and pipeline design.
- Build a culture of operational ownership where engineers take pride in pipeline reliability alongside feature velocity.
Required qualifications:
- Experience leading teams of 5–8 engineers building and operating data ingestion, ETL/ELT, or streaming pipelines in production.
- Deep understanding of streaming or event-driven data architectures (Kafka, Kinesis, Pub/Sub, or equivalent).
- Experience designing data normalization and enrichment pipelines at scale with strong attention to data quality, deduplication, and schema evolution.
- Proven ability to define and own SLOs for pipeline systems: latency, throughput, error rate, and data completeness.
- Experience operating data pipelines in cloud-native environments; understands failure modes and operational patterns at scale.
- Comfortable operating with autonomy; can translate ambiguous product requirements into well-scoped engineering projects.
- Proficiency in Go or Python; comfortable reading and writing pipeline code, not just managing those who do.
- Experience with message queues and streaming systems (Kafka, Kinesis, RabbitMQ, or equivalent).
- Experience with PostgreSQL or other relational databases as a pipeline destination.
- Kubernetes and containerized service operations in AWS or equivalent cloud.
- Familiarity with data observability tooling: pipeline monitoring, alerting, and schema drift detection.
Nice to have:
- Exposure to cybersecurity data (network scan data, vulnerability feeds, CVE/NVD schemas, asset inventories).
- Experience with graph data pipelines or knowledge graph construction.
- Familiarity with CDC (Change Data Capture) patterns for downstream data consumers.
- Background in data quality frameworks or data contract tooling.
Up to 5% travel may be required. Horizon3 is a fully remote company committed to diversity, equity, and inclusion.
