The Role

We’re looking for a Senior Staff Data Analyst to play a strategic role in defining, tracking, and influencing company-level KPIs, ensuring that key business decisions are backed by data. This role will be instrumental in generating insights across finance, marketing, product, customer support, and sales, helping leadership shape innovation, optimize customer experiences, and strengthen our market position.

Reporting directly to the VP of Data, this remote position will collaborate cross-functionally with stakeholders across the organization to turn data into actionable strategies. Additionally, this role will coach and mentor other analysts, ensuring high-quality data storytelling and executive communications for C-level reporting.

Responsibilities

Strategic Leadership & Business Impact

• Partner with senior leadership to define, track, and evolve company-wide KPIs that drive business performance.
• Deliver actionable insights that influence decision-making, experimentation, and prioritization across multiple teams.
• Present findings to executives and stakeholders in a clear, compelling, and data-driven manner to shape company strategy.
• Guide and mentor analysts in refining their storytelling and communication skills for C-level reporting.
• Manage multiple workstreams efficiently, balancing long-term initiatives with immediate business needs.

Data Analytics & Insights Generation

• Expertise in SQL to query, analyze, and transform data efficiently.
• Strong understanding of semantic layers to enable scalable, self-serve analytics across the company.
• Proficiency in Snowflake for data warehousing and advanced analytics.
• Advanced Tableau skills for building interactive dashboards and data visualizations.
• Experience with dbt (data build tool) is strongly desirable, as it enables efficient data transformation and modeling.
• Conduct data modeling and predictive analytics to support business initiatives.
• Apply A/B testing methodologies and experimental analytics to validate hypotheses and inform product development.
• Develop a foundational understanding of Python for analytics projects that require deeper data science techniques.
• Navigate GitHub to review key tables created by Engineering.
• Document insights and collaborate effectively using Confluence.

KPI Ownership & Cross-Functional Collaboration

• Own and influence company-level KPIs, ensuring alignment between business goals and data insights.
• Work closely with business stakeholders across finance, marketing, product, customer support, and sales to ensure data-driven decision-making is embedded into company strategy.
• Collaborate with Data Engineering to optimize data pipelines and improve reporting accuracy.
• Work with Analytics Engineering to create a business-facing semantic layer that enables scalable, reusable business insights and metrics.
• Partner with the Data Science team to transition insights into advanced models and deeper analyses.
• Maintain strong alignment with stakeholders through regular check-ins, meetings, and strategic planning sessions.
• Foster collaboration between Data, Engineering, and Business teams to drive holistic solutions.

Qualifications

• 8+ years of experience in business analytics, product analytics, or business intelligence, with a proven track record of supporting multiple business domains (finance, marketing, product, customer support, sales).
• Bachelor’s degree in Business, Economics, Statistics, Computer Science, Engineering, or a related field (Master’s degree preferred).
• Proven ability to define, track, and drive company-level KPIs, ensuring leadership decisions are grounded in data.
• Expertise in SQL, semantic layer architecture, Snowflake, and Tableau.
• Experience in A/B testing and experimental analytics for product and marketing optimization.
• Strong ability to present complex data clearly and persuasively to C-level executives and leadership teams.
• Demonstrated ability to coach and mentor analysts, especially in preparing insights and reports for C-level communications.
• Experience with dbt is strongly desirable, particularly for data transformation and modeling.
• Experience working with Analytics Engineering teams to design and maintain semantic layers for business-wide data accessibility.
• Excellent communication and collaboration skills, with a track record of working effectively across teams.
• Strong analytical and problem-solving mindset, with a passion for continuous learning and innovation.
• Flexibility to adapt to a fast-paced, evolving business environment.

Bonus Qualifications

• Familiarity with statistical analysis tools and techniques.
• macOS and G-Workspace knowledge is a plus!