Senior Analytics Engineer

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.

• Technical craftsmanship. You have extensive experience with dbt and modern data stack tooling – cloud data warehouses, ETL/rETL and BI tools. Fluent in SQL and ideally one data analytics language, e.g. python or R. You have a solid understanding of software engineering fundamentals in the context of data analytics code, and are able to effectively collaborate with data engineers at the infrastructure level.

• Analytics skills. You can parse complex business logic into elegant, performant data models, have strong instincts for defining and decomposing metrics, and are passionate about bringing quantitative perspective to business decisions.

• Cross-functional collaboration. You can communicate effectively with a range of technical and non-technical stakeholders, build a deep understanding of their context and business needs, and translate it into effective ways to empower them with data.

• Product-minded. You deeply care about the customer, and are passionate about using data to understand their experience with Dovetail and inform the direction of the product at both the tactical and strategic level.

• Pragmatic and flexible. You enjoy the uncertainty and unpredictability that comes with working in a startup, and know how to strike a balance between moving fast and building for the long term.