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Horizon3.ai

Autonomous pentesting SaaS for vulnerabilities

Engineering Manager - Data Streaming

Engineering LeadershipUpdated on Nov 13
Full-timeRemote in USA

About the Job

Requirements

  • Experience leading teams of 5–8 engineers building and operating data ingestion or ETL/ELT pipelines in production.
  • Deep understanding of streaming or event-driven data architectures, such as Kafka, Kinesis, or Pub/Sub.
  • Experience designing data normalization and enrichment pipelines at scale, including data quality, deduplication, and schema evolution.
  • Ability to define and own service-level objectives for pipeline systems, including latency, throughput, error rate, and data completeness.
  • Experience operating data pipelines in cloud-native environments and understanding their failure modes and operational patterns at scale.
  • Ability to translate ambiguous product requirements into well-scoped engineering projects.
  • Proficiency in Go or Python, including reading and writing pipeline code.
  • Experience with message queues and streaming systems such as Kafka, Kinesis, or RabbitMQ.
  • Experience with PostgreSQL or other relational databases as a pipeline destination.
  • Experience with Kubernetes and containerized service operations in AWS or an equivalent cloud.
  • Familiarity with data observability tooling for pipeline monitoring, alerting, and schema drift detection.

Responsibilities

  • Lead the Data Streaming sub-team within Data Ingestion, owning engineering execution and team health.
  • Drive sprint cadence, technical design reviews, and engineering quality for a team processing pentest telemetry at scale.
  • Own service-level objectives for ingestion throughput, latency, and error rates.
  • Build on-call processes and runbooks to keep pipelines healthy in production.
  • Maintain stable ingestion schemas and data contracts between the NodeZero runner, Security Research, and the Database Platform, evolving these contracts as new pentest capabilities ship.
  • Scale ingestion pipelines to support customer growth, larger environments, and new data types without a proportional increase in operational engineering effort.
  • Work with Security Research, Database Platform, and Asset Inventory to align on data quality and pipeline design.
  • Grow the Data Streaming sub-team to full capacity and foster operational ownership of pipeline reliability.

Desired Qualifications

  • Exposure to cybersecurity data, including network scan data, vulnerability feeds, CVE/NVD schemas, or asset inventories.
  • Experience with graph data pipelines or knowledge graph construction.
  • Familiarity with Change Data Capture patterns for downstream data consumers.
  • Background in data quality frameworks or data contract tooling.

About the Company

Horizon3.ai

Autonomous pentesting SaaS for vulnerabilities

Horizon3.ai specializes in cybersecurity by offering NodeZero, a SaaS platform for autonomous penetration testing. It lets enterprises simulate cyber-attacks on their own systems in a self-service way, without installing persistent agents, and without ongoing human intervention. The platform works by running security-focused attack simulations in production environments to uncover exploitable vulnerabilities and weak controls, delivering vulnerability assessments, threat simulations, and compliance-oriented testing through tiered subscription plans. This approach differentiates Horizon3.ai from traditional pentesting by being self-service, agentless, and safe to run in live environments, while targeting enterprise customers that must meet standards such as PCI DSS. The company aims to help organizations improve their security posture, prioritize remediation, and maintain regulatory compliance by continuously identifying and fixing weaknesses.

Company size
501-1,000
Company stage
Series E
Total funding
$437M
Headquarters
San Francisco, CA
Founded
2019

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