Senior Data Engineer

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 we’re looking for a Senior Data Engineer who is passionate about making our data stack great to interact with, and who enjoys optimising pipeline setups to keep up with the latest & greatest standards.

Think of this role as bridging the Data Engineer & Analytics Engineer domains (but weighted more towards the former). As an early stage startup, and the first hire in this area, you’ll get the chance to meaningfully impact every part of our stack and set the technical direction.

What you’ll be doing:

• Making our CI/CD process great, enabling Engineering & Data to develop & deploy code quickly and with confidence. This is critical to help our team scale and is an area where you can quickly have a lot of impact.

• Being the glue between Engineering and Data, proactively working with users of our data stack to understand where gaps & improvements are, and building strong relationships across the company.

• Owning & improving the “EL” part of our stack (currently Fivetran, Segment, and some Python scripts), being responsible for accelerating our teams whilst also setting technical direction, trading off “build vs. buy”, and keeping costs under control.

• Improving the “T” part of our stack, helping make our dbt setup exceptional. All of our Data team are well versed in dbt, so you won’t be expected to “own” dbt - but level up how we use it as a team.

• Establishing best practices across the company, including pipeline testing, documentation and scalability to elevate overall data quality and team confidence.

This role could be ideal for you if you:

• Have a strong background in end‑to‑end data engineering, ideally in both early stage and larger companies, and know what works (and what doesn’t!).

• Are an expert on dbt Core, and are comfortable with advanced concepts such as overriding default macros (e.g. schema name generation), complexities with implementing incremental models, and state deferral.

• Thrive in owning the full Data Engineering lifecycle, from technical architecture through to stakeholder engagement - and setting long-term direction.

• Are comfortable evaluating “build vs. buy” decisions, optimising for performance, cost and maintainability.

• (Optional) Bring hands-on experience with GCP and Terraform, to collaborate effectively with our infrastructure 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