Analytics Engineer

About Zego

At Zego, we understand that traditional motor insurance holds good drivers back. It's too complicated, too expensive, and it doesn't reflect how well you actually drive. Since 2016, we have been on a mission to change that by offering the lowest priced insurance for good drivers.

From van drivers and gig workers to everyday car drivers, our customers are the driving force behind everything we do. We've sold tens of millions of policies and raised over $200 million in funding. And we're only just getting started.

Overview of Team

The Data team at Zego partners with the business to maximise the value of data. Through collaborative engineering and analytics, we ensure our teams are equipped with relevant and reliable insights to drive fast, confident and high-impact decisions.

We're a small, dynamic team responsible for all aspects of data — availability, quality, integration, problem formulation, success metrics, reporting, and analytics. We take an AI-First approach: AI is now central to how we work, and we focus less on hand-writing code and more on framing problems, specifying intent, and owning the trust infrastructure (testing, contracts, observability) that the business relies on.

About the Role

We're looking for an Analytics Engineer who's genuinely excited about how this craft is changing. The way we build is shifting: AI tools now handle a lot of the heavy lifting of writing SQL and boilerplate, which means the job is increasingly less about typing code and more about understanding the business problem, specifying what "good" looks like, and making sure what we ship is correct and trustworthy.

In practice, that means you'll design and build data models with the support of AI-assisted workflows, and you'll own a growing share of the testing, data contracts, and observability that let the rest of the business rely on our data with confidence. You'll work closely with senior engineers and stakeholders, with plenty of room to grow your technical depth and take on more ownership over time.

You'll have a solid technical foundation, a natural curiosity for data, and a healthy instinct to question whether a number is actually right — not just whether a query ran.

What You Will Be Doing

Data Modelling & Engineering (AI-assisted)

Work with stakeholders to understand business needs and translate them into clear, well-scoped requirements

Build and maintain robust data models and exposures in dbt, Snowflake, and Looker — using AI-assisted development to move faster, spending less time hand-writing boilerplate and more time specifying intent, reviewing, and refining

Read, debug, and critically review SQL (including AI-generated code), so we ship models we can trust

Document modelling decisions, trade-offs, and outcomes clearly

Wrangle and integrate data from multiple third-party sources (e.g. Amplitude, Segment, Google Ads)

Data Quality, Trust & Operations

Help build and maintain the "trust infrastructure" — tests, data contracts, and observability — that lets the business depend on our models

Ensure quality, reliability, and stability across data models and pipelines

Create secure, efficient data shares for external partners (e.g. S3, SFTP, Snowflake Data Sharing)

Contribute to the continuous improvement of our data platform, tooling, and ways of working — including how we use AI in our workflows

Stakeholder Enablement

Support business users across the company to promote a culture of data-driven decision-making

Help translate business questions into well-designed data solutions and metrics

Help enable and maintain self-service capabilities within our BI tools

About You

You'll have around 1–3 years' experience as an Analytics Engineer or in a similar role

You'll have solid SQL skills — comfortable reading, writing, debugging, and critically reviewing queries (including AI-generated ones); experience with dbt and/or Looker is a plus

You'll have some familiarity with modern data platforms (e.g