Senior Product Analytics Engineer
New
H
Horizon3Cybersecurity analytics
US, RemoteFull-TimeSenior
SalaryBase salary range is $142,718-$186,560. Additional compensation: All full-time roles are eligible for an equity package in the form of stock options.
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Job Details
- Experience
- 7+ years of experience spanning data engineering and analytics, ideally in a role bridging both
- Required Skills
- SQLMicrosoft Power BITableauProduct AnalyticsData modelingdbtLooker
Requirements
- 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 skills.
- Hands-on experience with dbt.
- Hands-on experience building production data pipelines.
- Experience building stakeholder-facing analytics or dashboards.
- Experience translating ambiguous business requirements into governed, well-documented data models.
- Preferred: experience partnering with product or engineering teams on instrumentation and source data design.
- Preferred: experience contributing to data governance or metrics certification.
- Preferred: familiarity with Tableau, Looker, or Power BI.
- Preferred: experience with AWS, GCP, or Azure.
- Preferred: experience with Git-based workflows and CI/CD for data pipelines.
Responsibilities
- Design, build, and maintain scalable ELT pipelines and data models for product usage and event telemetry.
- Partner with Product Engineering on the canonical product data layer and accurate product usage and behavioral signal definitions.
- Support data taxonomy definition, metric certification, and governance-standard documentation.
- Build and own the semantic layer and self-service data models for Product Analytics.
- Own data quality monitoring and anomaly detection for product usage data, partnering with Data Engineering on pipeline or platform issues.
- Build pipelines and models for expansion and upsell cohorts, usage thresholds, feature adoption, and seat utilization metrics.
- Help define analytics standards and tooling enablement, and align Product Analytics practices with company-wide methodology.
- Present technical data concepts and business implications to engineering, non-technical stakeholders, and leadership.
- Drive engineering best practices within Product Analytics data assets.
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