Job description

Get to Know Us Horizon3 is a fast-growing, remote cybersecurity company dedicated to the mission of enabling organizations to proactively find and fix and verify exploitable attack vectors before criminals exploit them. Our flagship product, the NodeZeroTM platform, delivers production-safe autonomous pentests and other key assessment operations that scale across the largest internal, external, cloud, and hybrid cloud environments. NodeZero has been adopted by organizations of all sizes, from small educational institutions to government agencies and Global 100 enterprises. It is used by ITOps/SecOps teams, consulting pentesters, and MSSPs and MSPs. We are a fusion of former U.S. Special Operations cyber operators, startup engineers, and formerly frustrated cybersecurity practitioners. We're committed to helping solve our common security problems: ineffective security tools, false positives resulting in alert fatigue, blind spots, "checkbox” security culture, cybersecurity skills shortage, and the long lead time and expense of hiring outside consultants. Collectively, we are a team of learn it alls, committed to a culture of respect, collaboration, ownership, and results. What You'll Do: Horizon3 is investing in a company-wide data strategy to make our data trusted, governed, and built to power revenue growth. The Senior Product Analytics Engineer sits at the center of that effort: you're the bridge between how product data is modeled and built and how it's trusted and used across the company. You'll work hand-in-hand with Data Engineering to help shape the canonical product data layer at the source, with the emerging Data Governance function to get metrics certified and documented, and with the Product analysts and PMs to turn that foundation into self-service, decision-ready data products. You're equally comfortable writing a dbt model, troubleshooting a pipeline, and helping a non-technical stakeholder define a company wide KPI. Key Responsibilities: - Design, build, and maintain scalable ELT pipelines and data models that translate 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 signal definitions are built on accurate, governed source data, not just what's convenient downstream. - Partner with the new Data Governance function: support taxonomy definition work, prepare metrics for certification, and maintain documentation to governance standards (including AI/machine-readable structure). - Build and own the semantic layer and self-service data models for Product Analytics, so internal stakeholders can query with confidence without needing a SQL expert in the room every time. - Own data quality monitoring and anomaly detection for product usage data specifically, partnering with Data Engineering when issues trace back to pipeline or platform-level causes. - Contribute analytics engineering support to the expansion/upsell cohort work, building the pipelines and models that turn usage thresholds, feature adoption, and seat utilization into certified, production-grade metrics. - Collaborate with data people across the company to help define analytics standards and tooling enablement and then ensure Product Analytics' practices align with the company-wide methodology as it matures. - Present technical data concepts and their business implications clearly to both engineering and non-technical stakeholders, including leadership. - Drive engineering best practices within the Product Analytics team's data assets. What You'll Bring: - A builder's mindset for data — you enjoy shaping how product data is modeled at the source, not just querying what already exists - Comfort moving fluidly between technical and business conversations - A governance driven approach to data. You default to documenting, defining, and getting alignment on what a metric means, rather than shipping something that "mostly works" - Bias toward self-service, you build data models assuming someone else will need to understand and trust them without you in the room - Curiosity and ownership when something looks off in the data - Adaptability in a fast-paced, evolving data environment and comfortable building foundational structure while priorities and requirements are still taking shape Required Education/Experience: - Bachelor's degree or equivalent in Computer Science, Engineering, Information Systems, or a 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 Education/Experience: - Proven experience partnering directly with product/engineering teams on instrumentation and source data design — not just consuming what's handed downstream - 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) Perks of Horizon3 - Inclusive Team: We value diversity and promote an inclusive culture where everyone can thrive. - Growth Opportunities: Be part of a dynamic and growing team with numerous career development opportunities. - Innovative Culture: Work in a collaborative environment that encourages creativity and out-of-the-box thinking. - Hybrid & Remote Work: We embrace a mix of remote and hybrid work models depending on role and location, including our Chicago office, where some roles require regular in-office presence. - Competitive Compensation: We offer competitive salary, equity and benefits. Our benefits include health, vision & dental insurance for you and your family, a flexible vacation policy, and generous parental leave. Compensation and Values At Horizon3, we believe that our people are our greatest asset, and our compensation philosophy reflects this core value. We are committed to fostering an environment where all employees feel valued, respected, and rewarded for their contributions. Our compensation structure is designed to be fair, competitive, and transparent, ensuring that every team member is recognized and compensated equitably across roles, levels, and locations. In accordance with various State’s transparency regulations, we provide the following salary range information for this position: - Base salary range is $142,718-$186,560. The exact salary will be determined based on the selected candidate’s location, qualifications, experience, and relevant skills. - Additional compensation: All full-time roles are eligible for an equity package in the form of stock options. You Belong Here Horizon3 is not just an equal opportunity employer - we are a community that values diversity, equity, and inclusion as fundamental principles of our culture and success. We are dedicated to fostering a workplace where everyone feels welcome and respected, regardless of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, hair length or any other legally protected status by law. Our commitment to diversity and inclusion means we strive to attract, develop, and retain a workforce that reflects the varied communities we serve. We believe that diverse perspectives drive innovation and strengthen our ability to create cutting-edge cybersecurity solutions. At Horizon3, every team member is valued and supported in an environment that encourages personal and professional growth. We welcome candidates from all backgrounds and experiences, and we encourage all qualified individuals to apply. Come be a part of Horizon3, where your unique contributions are recognized, and your potential is limitless. Other Duties Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Duties, responsibilities, and activities may change at any time with or without notice. Application Note In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Requirements

Must-haves

Get to Know Us
Design, build, and maintain scalable ELT pipelines and data models that translate 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 signal definitions are built on accurate, governed source data, not just what's convenient downstream.
Partner with the new Data Governance function: support taxonomy definition work, prepare metrics for certification, and maintain documentation to governance standards (including AI/machine-readable structure).
Build and own the semantic layer and self-service data models for Product Analytics, so internal stakeholders can query with confidence without needing a SQL expert in the room every time.
Own data quality monitoring and anomaly detection for product usage data specifically, partnering with Data Engineering when issues trace back to pipeline or platform-level causes.
Contribute analytics engineering support to the expansion/upsell cohort work, building the pipelines and models that turn usage thresholds, feature adoption, and seat utilization into certified, production-grade metrics.
Collaborate with data people across the company to help define analytics standards and tooling enablement and then ensure Product Analytics' practices align with the company-wide methodology as it matures.
Present technical data concepts and their business implications clearly to both engineering and non-technical stakeholders, including leadership.
Drive engineering best practices within the Product Analytics team's data assets.
A builder's mindset for data — you enjoy shaping how product data is modeled at the source, not just querying what already exists
Comfort moving fluidly between technical and business conversations
A governance driven approach to data. You default to documenting, defining, and getting alignment on what a metric means, rather than shipping something that "mostly works"
Bias toward self-service, you build data models assuming someone else will need to understand and trust them without you in the room
Curiosity and ownership when something looks off in the data
Adaptability in a fast-paced, evolving data environment and comfortable building foundational structure while priorities and requirements are still taking shape
Bachelor's degree or equivalent in Computer Science, Engineering, Information Systems, or a 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
Proven experience partnering directly with product/engineering teams on instrumentation and source data design — not just consuming what's handed downstream
Experience standing up or contributing to a data governance or metrics-certification process
Familiarity with BI/visualization tools (Tableau, Looker, Power BI)

Nice-to-haves

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Application prep

Use the role’s language and application details while tailoring your materials.

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Benefits

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Dental

Vision

Parental Leave