SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 142,718 - 186,560 / annual
Horizon3.ai is a fast-growing remote cybersecurity company building NodeZero, an autonomous penetration testing platform that helps organizations proactively identify and fix exploitable attack vectors. The company is founded by former U.S. Special Operations cyber operators and startup engineers, serving organizations from educational institutions to Global 100 enterprises.
As Senior Product Analytics Engineer, you will be the bridge between product data modeling and trusted, governed data usage across the company. You'll sit at the center of Horizon3's company-wide data strategy, working hand-in-hand with Data Engineering, the emerging Data Governance function, and Product teams to build a canonical product data layer and self-service analytics infrastructure.
Key responsibilities include:
- Design, build, and maintain scalable ELT pipelines and data models translating raw product usage and event telemetry into trusted, well-documented analytics assets
- Partner with Product Engineering on the canonical product data layer, ensuring product usage cohorts and behavioral signals are built on accurate, governed source data
- Support the Data Governance function with taxonomy definition, metrics certification, and documentation to governance standards
- Build and own the semantic layer and self-service data models for Product Analytics, enabling internal stakeholders to query with confidence
- Own data quality monitoring and anomaly detection for product usage data, partnering with Data Engineering on pipeline-level issues
- Contribute to expansion/upsell cohort work, building production-grade metrics around usage thresholds, feature adoption, and seat utilization
- Collaborate across the company to define analytics standards and ensure Product Analytics aligns with company-wide methodology
- Present technical data concepts and business implications clearly to engineering and non-technical stakeholders
- Drive engineering best practices within the Product Analytics team's data assets
You should have a builder's mindset for data, comfort moving between technical and business conversations, and a governance-driven approach that defaults to documenting and defining metrics rather than shipping quick solutions. You thrive in self-service environments, are curious when data looks off, and adapt well to fast-paced, evolving environments.
REQUIREMENTS:
- Bachelor's degree or equivalent in Computer Science, Engineering, Information Systems, or related field
- 7+ years of experience spanning data engineering and analytics, ideally in a role bridging both
- Advanced SQL and hands-on experience with dbt
- Hands-on experience building both production data pipelines and stakeholder-facing analytics/dashboards
- Experience translating ambiguous business requirements into governed, well-documented data models
PREFERRED:
- Proven experience partnering directly with product/engineering teams on instrumentation and source data design
- Experience standing up or contributing to a data governance or metrics-certification process
- Familiarity with BI/visualization tools (Tableau, Looker, Power BI)
- Experience with cloud platforms (AWS, GCP, Azure)
- Experience with Git-based workflows and CI/CD for data pipelines
- Regular use of AI in coding/development workflows (agents, memory files, copilots)
