Data & Insights

Accountabilities: Partner with Product and Engineering teams to identify opportunities, define meaningful metrics, run experiments, and influence roadmap decisions. Translate ambiguous or complex business and product questions into rigorous analysis, actionable insights, and measurable improvements. Collaborate with the Head of Data on data architecture, foundations, tooling, and the long-term evolution of the data environment. Develop and improve data models, pipelines, instrumentation, and analytics workflows as business and product requirements evolve. Evaluate when to build internal solutions, purchase existing tools, or adopt lightweight approaches to solve data challenges efficiently. Help advance the internal data agent, making it more useful, accessible, and valuable to teams across the organization. Enable teams across the business to become more autonomous and effective in accessing, understanding, and applying data. Identify opportunities to improve the reliability, accessibility, and usability of data and analytics. Balance technical depth with practical business judgment, prioritizing solutions based on their expected impact. Contribute to the continuous improvement of data practices, processes, and tooling within a modern, evolving data environment. Requirements Strong experience in data analytics, insights, data engineering, product analytics, or a closely related discipline. Strong SQL skills and solid knowledge of data modeling, analytics, and modern data tooling. Ability to work comfortably across both analytical problems and data foundations, including models, pipelines, instrumentation, and practical internal tools. Product-oriented mindset with genuine curiosity about user behavior, product performance, and how data can improve decision-making. Strong ownership and judgment, with the ability to take an ambiguous problem, determine the right approach, and move it toward a practical solution. Ability to assess when to move quickly, investigate deeply, build, buy, or keep a solution intentionally simple. Strong analytical thinking and the ability to turn raw or messy data into clear recommendations and measurable outcomes. Excellent communication and collaboration skills, with the ability to work effectively with Product, Engineering, Growth, Marketing, and senior leadership. Confidence challenging assumptions constructively and communicating complex findings clearly to both technical and non-technical stakeholders. Strong bias toward measurable impact, with a focus on what changes as a result of your work rather than simply what gets delivered. Experience with modern data technologies is valuable, particularly GCP, BigQuery, Composer, dbt, Tableau, Count, Amplitude, Segment, or similar tools. Familiarity with AI-powered data tools, internal data agents, or data applications is a plus. Willingness and ability to learn new technologies and continuously evolve your technical toolkit. Benefits Highly autonomous role with significant freedom to identify opportunities and shape solutions. Broad scope spanning product analytics, business insights, data foundations, experimentation, and AI-enabled data tools. Direct influence on product strategy, company metrics, roadmap decisions, and growth initiatives. Opportunity to shape data architecture, tooling, processes, and the way teams across the organization use data. Remote-first working environment across Europe, with flexibility around location. Opportunity to work with a modern data stack including GCP, BigQuery, dbt, Replit, Tableau, Count, Amplitude, and Segment. Collaborative environment spanning Product, Engineering, Growth, Marketing, Data, and leadership. Opportunity to work at a profitable, growing technology company serving thousands of teams and millions of users. Significant opportunity for professional growth through ownership of high-impact, cross-functional initiatives. A culture centered on autonomy, experimentation, practical problem-solving, and measurable impact.