Product Data Analyst

About incident.io

incident.io is the leading all-in-one platform for incident management. From small bugs to major outages, incident.io helps teams respond fast, reduce downtime, and improve every time something goes wrong.

Since launching in 2021, we’ve helped 800 companies—including Netflix, Airbnb and Block—resolve over 250,000 incidents. Every month, more than 30,000 responders across Engineering, Product and Support use incident.io to fix things faster.

We’re a small team that cares deeply about pragmatism, quality, magic, and pace. We've raised $100M from Index Ventures, Insight Partners and Point Nine, alongside many angel investors who are founders and executives of world-class companies.

The Team

At incident.io we collect a variety of data both internally (product usage) and externally (social media, Google Analytics, Stripe, Finance & Sales tools), and we’re really proud of the data stack we’ve built so far - which consists of Google BigQuery, Fivetran, dbt, and Omni.

Our Data team is doubling this year, and as our second Product Data Analyst you’ll be embedded directly within our Product function - working closely with engineers and product managers to turn data into clear, actionable insights that shape feature prioritisation, UX improvements, and roadmap decisions.

Because we’re still early in our growth, this role bridges the Analytics Engineering and Data Analytics domains - with more emphasis on the latter. You’ll have huge scope to define projects, dig into the full breadth of our data, and see your recommendations drive real business outcomes. See Matilda’s (Product Data Analyst) recent LinkedIn post on our industry benchmark report to get more insight into the types of data you’ll get to work with!

What you’ll be doing:

• Partnering closely with product managers and engineers, translating hypotheses and roadmap goals into clear analyses such as a new onboarding flow, diagnosing drop‑off in a feature, or benchmarking performance across cohorts.

• Building and maintaining data models in BigQuery & dbt, designing modular, tested dbt models that capture key product data, user journeys, and feature flags.

• Developing reports in Omni, allowing product managers to track adoption, engagement, and retention metrics.

• Running ad-hoc analyses, translating findings into clear recommendations, or areas to dig into further.

• Evangelising data best practices across Product, ensuring metrics consistency and analytical rigor in decision-making.

This role could be ideal for you if you:

• Have a strong foundation in data analytics / science / analytics engineering practices, and are comfortable wearing both “analyst” and “engineer” hats in a fast‑paced environment.

• Are very comfortable using dbt (SQLMesh is also highly relevant), including building and maintaining data pipelines and setting up robust tests.

• Have strong product intuition & communication, ask the right questions to frame analyses, and you can distill complex results into succinct, non‑technical narratives.

• Are a self-starter, and spot high‑leverage opportunities and can drive them end‑to‑end, and can balance quick wins with long‑term projects.

• Thrive in a fast-paced environment and enjoy shaping processes as part of a small, growing team.

What we offer:

We’re building a place where great people can do their best work—and that means looking after you and your family with benefits that support health and personal growth.

• Market leading private medical insurance

• Generous parental leave

• First Friday of the month off

• Generous annual leave/PTO allowance

• Competitive salary and equity

• Remote working and personal development budget

• Enhanced pension/401k