Dovetail is the world’s leading AI-first customer insights hub, on a mission to improve the quality of every thing. We’re redefining what it means to be connected to your customer, giving everyone on the product team fast and easy access to customer insights at any point in the development lifecycle.
Founded in 2017, Dovetail’s team is 100+ and growing across our offices in Sydney and San Francisco. We’re seeking ambitious problem solvers from a diverse range of backgrounds, who are desired for their experience, passionate about their craft, and excited about the work we’re undertaking. If this sounds like you, read on…
The Data team’s mission is to enable teams across Dovetail with accurate and useful data, bringing clarity and structure to decision making across the business. We are looking for a Senior Analytics Engineer to take ownership of our data warehouse architecture and data pipelines powering a range of dashboards, reports and data syncs to operational systems. You will join at a critical time in the team’s journey, as we undertake a large scale effort to overhaul our data platform and tooling to prepare for the next stage of growth for Dovetail. You will drive the technical direction of Dovetail’s data platform as the company scales, and work closely with product and GTM teams to continuously improve their data practices.
Our data stack: Fivetran, Segment, Postgres, Snowflake, dbt, Census, Metabase.

• Own Dovetail’s dbt pipeline and data warehouse architecture. Apply engineering best practices to build analytics models that are reusable, tested and performant.
• Distill complex business logic into clean abstractions and metrics. Drive alignment across teams on how we quantitatively understand the state of the product and the business.
• Constantly learn, innovate and raise the bar of how we do data at Dovetail. This may involve exploring advanced features of our data tools, designing new ways to organise and model our data, or leading the adoption of new tools and practices across the organisation.
• Work cross-functionally with a range of stakeholders. Ensure data is leveraged effectively: with product teams to help define and instrument product metrics and KPIs, with finance teams to enable detailed revenue reporting, and with leadership to answer key strategic questions.
• Provide technical leadership and mentorship within the data team. Work closely with data engineers and data scientists to ensure the right data is captured and exposed to downstream applications, including for advanced analytics and predictive modelling. Tackle complex problems around performance, scalability and accuracy, making pragmatic tradeoffs as needed.
• Operate outside of your direct remit. Get involved in product analytics and predictive modelling work, setting up dashboards and data integrations, and collaborating with engineers on events tracking and experimentation.