Analytics Engineer, Doodle

• You are more than an Analytics Engineer
• You are a builder who cares about getting the numbers right, and you love helping people make better decisions with them
• You’ll thrive here if you combine strong analytics engineering fundamentals with a product and business mindset, and you’re honest about your strengths, gaps and what you’re still learning
• The Modelling Experience: Strong, hands-on experience building analytics data models with dbt or a similar transformation framework, and a good grasp of dimensional modelling
• The SQL: Advanced SQL skills and experience working with large analytical datasets
• The Warehouse: Experience with cloud data warehouses such as Amazon Redshift
• The BI Toolkit: Experience building dashboards and self-service reports in Power BI or similar BI tools
• The Product Lens: Familiarity with experimentation frameworks and product analytics
• The AI Mindset: Hands-on experience with Claude or similar AI assistants, including setting up MCPs and using AI coding tools. You’ve helped drive AI adoption in a team or organisation
• The Communicator: You can explain technical concepts to technical and non-technical people alike, and turn data into recommendations that help stakeholders decide
• The Location: You are based in, and have the right to work in, the country where this role is advertised. We cannot sponsor visas or support relocation at this time

Desirable

• Doodle is a B2B SaaS platform used by millions of professionals to coordinate meetings and collaboration across teams and companies
• We are building the future of scheduling and productivity, and trusted data has become one of our most valuable products
• Every product decision, experiment, customer insight and business metric depends on it
• In this role, you’ll co-own a share of the analytics layer that powers decisions across Doodle
• You’ll turn raw product data into trusted, scalable datasets for experimentation, reporting and product innovation
• Our transformations are built in dbt on top of Amazon Redshift, with Athena alongside it, and teams explore and report on data in Power BI, Hex and our own internal AI tools
• You’ll work closely with Product, Engineering, Sales, Marketing, Finance and Leadership
• Some days that means defining the metrics the whole company runs on
• Other days it means helping a Growth Manager design an A/B test, or showing a team how to answer their own questions without waiting on anyone
• If you get excited by clean models, well-defined metrics and data people actually trust, you’ll find a stimulating environment here
• AI is at the heart of how we work
• We expect you to use AI coding tools to move faster on modelling, testing and documentation, and to help the rest of Doodle get more out of AI in their daily work with data
• Model the Data: Design, build and maintain scalable analytics data models in dbt, following analytics engineering best practices
• Own Data Quality: Build reliable transformations from raw product data to business-ready datasets, with testing, validation and documentation across the analytics layer
• Define the Metrics: Define, document and maintain the trusted business metrics used across the company, and keep definitions aligned across teams
• Build the Semantic Layer: Evolve a scalable semantic layer that makes consistent reporting and self-service analytics possible
• Power Experimentation: Partner with Product and Growth Managers on A/B tests, funnels, retention and customer insights, through high-quality event modelling and instrumentation. Then help teams read the results and decide what to do next
• Measure What Matters: Give product launches and feature rollouts reliable measurement frameworks from day one
• Enable Self-Service: Build dashboards and reports in Power BI, Hex or our internal AI tools, and coach stakeholders so they can find their own answers
• Lead with AI: Build AI-enabled analytics workflows and help teams across Doodle adopt AI in how they work with data

• We usually respond within two weeks
• Initial Application Review
• HR Interview
• Technical Interview (based on Home Assignment)
• Exec Interview
• Final Offer & Reference Check