Senior Product Analytics Engineer

Role overview

A remote cybersecurity company is investing in a company-wide data strategy to make its data trusted, governed, and built to support revenue growth. The Senior Product Analytics Engineer sits at the center of that effort, acting as the bridge between how product data is modeled and built, and how it is trusted and consumed across the business. The role partners closely with data engineering, an emerging data governance function, and product analysts and PMs to turn foundations into self-service, decision-ready data products.

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 rest on accurate, governed source data. - Collaborate with the data governance function to support taxonomy definition, prepare metrics for certification, and maintain documentation to governance standards. - Build and own the semantic layer and self-service data models so internal stakeholders can query with confidence without a SQL expert in the room. - Own data quality monitoring and anomaly detection for product usage data, partnering with data engineering when issues trace back to pipeline or platform causes. - Support expansion and upsell cohort work by turning usage thresholds, feature adoption, and seat utilization into certified, production-grade metrics.

Requirements

- A builder's mindset for data, with comfort shaping how product data is modeled at the source rather than only querying what already exists. - Ability to move fluidly between technical implementation and business conversations with non-technical stakeholders, including leadership. - A governance-driven approach: defaulting to documenting, defining, and aligning on what a metric means before shipping. - Bias toward self-service, building data models assuming someone else will need to understand and trust them without you present. - Hands-on experience with dbt-style transformation workflows, modern ELT pipelines, and analytics engineering best practices. - Curiosity, ownership, and adaptability in a fast-paced, evolving data environment.

Benefits and work setup

- Fully remote work environment. - Medical, dental, and vision insurance for the employee and family. - Flexible vacation policy and generous parental leave. - Equity package in the form of stock options for all full-time roles. - Base salary range of $142,718 to $186,560, with the exact figure determined by location, qualifications, experience, and relevant skills.