Join Knapsack to turn product usage and delivery data into meaningful, actionable insights — helping us learn faster, build smarter, and deliver better.

About Knapsack

Knapsack is building the AI Product Engine — a platform that helps teams eliminate the gap between what they design and what they build. We do that by grounding every tool, agent, and workflow in a living, intelligent source of truth.

We integrate structured design systems, development workflows, and LLM-powered assistants to help organizations scale digital product delivery with clarity and confidence.

As we grow, we’re collecting valuable data across tools like Snowflake, Segment, HubSpot, Datadog, Linear, and DoubleLoop. We now need sharper visibility into what that data means, where it signals value or friction, and how it can guide product direction and engineering performance.

Overview

We’re hiring a Product Data Analyst to lead the development of our internal insight function. This is a mid-level role for someone with 3–5 years of experience working with product, customer, or operational data — and a passion for helping cross-functional teams make faster, better-informed decisions.

You’ll partner with product, engineering, customer success, and leadership to help define what we measure, why it matters, and how we learn from it. Your work will influence both what we build and how we build it — from user behavior and product engagement to quality, velocity, and delivery cycle time.

What we think you’ll do

• Define and maintain core product metrics (activation, engagement, retention, expansion)
• Build clear, trustworthy reporting from tools like Snowflake, Segment, HubSpot, Linear, Datadog, and DoubleLoop
• Create and maintain internal dashboards focused on quality, delivery speed, cycle time, and engineering throughput
• Surface insights that inform product prioritization and roadmap validation
• Help customer teams identify patterns of adoption, friction, and churn risk
• Support diagnostics of key experiments, initiatives, and usage patterns
• Align product and delivery metrics with company goals and strategy

What we think you’ll need

• 3–5 years of experience in analytics, product data, or business intelligence roles
• Strong SQL fluency and experience working in modern data warehouses (Snowflake preferred)
• Hands-on experience with Segment or equivalent event tracking pipelines
• Familiarity with tools like HubSpot, Linear, Datadog, and experience extracting and joining operational data
• Ability to clearly communicate complex findings to diverse stakeholders (product, eng, exec)
• Curiosity, independence, and a bias toward insight over reporting

Bonus points for

• Experience using DoubleLoop, or other outcome-aligned strategy tools
• Familiarity with reverse ETL (e.g., syncing data back into tools like HubSpot, Slack, or CRMs)
• Exposure to dbt-style modeling — using SQL frameworks to define reusable product data sets
• Experience running cohort analysis, funnel diagnostics, or lifecycle segmentation
• Knowledge of delivery metrics such as DORA, cycle time, or issue flow analysis
• Previous work with developer tools, SaaS platforms, or product-led growth environments

Why this role matters

We already collect rich product and engagement data — but insight without action doesn’t drive outcomes. This role is about creating the connective tissue between what we see and what we do.

You’ll give the team shared visibility, sharpen our instincts, and help make better decisions faster — from roadmap validation to customer engagement to how we scale delivery.

Location

Remote-friendly (US-based). Knapsack is a fully remote company, headquartered in Portland, OR.

Compensation & Benefits

• Salary range for this role is $110,000 - $140,000
• Equity
• Flexible, remote-first work culture
• Unlimited PTO
• Medical, dental, and vision insurance fully covered by the Company
• A thoughtful, ambitious team building something truly original