Senior Product Analytics Engineer — Remote & Equity

Horizon3.ai; United States; Hybrid; USD 143,000 - 187,000; Full time

Benefits offered by this job

Inclusive team

Growth opportunities

Innovative culture

Hybrid & Remote work

Competitive compensation

Job summary

Horizon3 is seeking a Senior Product Analytics Engineer to bridge product data modeling and trusted analytics across the company. You will help shape the canonical product data layer with Data Engineering and Data Governance, turning raw usage into self-service data products.

You will write dbt models, troubleshoot pipelines, and collaborate with Product analysts and PMs to define KPIs and ensure governance and lineage.

Qualifications

• 7+ years of experience spanning data engineering and analytics, bridging both.
• Advanced SQL and hands-on experience with dbt.
• Experience building production data pipelines and stakeholder-facing analytics.
• Ability translate ambiguous business requirements into governed, well-documented data models.
• Strong collaboration with product/engineering teams on instrumentation and source data design

Responsibilities

• Design, build, and maintain scalable ELT pipelines and data models.
• Partner with Product Engineering on the canonical data layer and governance.
• Support taxonomy and metrics certification with Data Governance.
• Build semantic layer and self-service data models for Product Analytics.
• Own data quality monitoring and anomaly detection for product data.
• Contribute analytics engineering to expansion/upsell cohorts and metrics.
• Help define analytics standards and tooling across the company.
• Present data concepts to engineers and leadership.
• Drive best practices within the Product Analytics data assets.

Skills

Advanced SQL

dbt

Data modeling

Analytics engineering

Stakeholder communication

Education

Bachelor's degree or equivalent in CS/Engineering/IS

Tools

dbt

Job description

Horizon3 is seeking a Senior Product Analytics Engineer to bridge product data modeling and trusted analytics across the company. You will help shape the canonical product data layer with Data Engineering and Data Governance, turning raw usage into self-service data products.

You will write dbt models, troubleshoot pipelines, and collaborate with Product analysts and PMs to define KPIs and ensure governance and lineage.