Data & Insights

This is a highly autonomous data role at the intersection of product, business, engineering, and analytics.
You will turn complex and sometimes ambiguous questions into actionable insights that improve product and company performance.
Your work will directly influence product priorities, experiments, growth initiatives, metrics, and data-driven decision-making.
You will contribute both to hands-on analysis and to the evolution of data foundations, models, pipelines, instrumentation, and tooling.
You will work closely with Product, Engineering, Growth, Marketing, and leadership while helping teams become more effective and self-sufficient with data.
The role also offers the opportunity to shape how AI and internal data tools are used across the organization.
With broad ownership and freedom to build, buy, or simplify solutions, you will have substantial influence over both the data strategy and how data creates measurable impact.

• 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.