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Senior Product Analytics Engineer

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Salary

Base salary range is $142,718 - $186,560.

Location

US, Remote

Posted

Today

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.

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)

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