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Tier-1 brand, metro location, mid-level generalist analytics role with broad skillset increases applicant competition.
SaaS-specific KPIs and analytics engineering skills moderately limit cross-industry transferability.
Explicit 3+ years requirement plus mandatory Snowflake, SQL, and BI stack tightens shortlisting.
Develop and maintain production-grade SQL models, data pipelines, and dashboards that support retention, expansion, and growth decisions across the business.
Partner with Data Engineering, Data Science, and business stakeholders to define reliable metrics and translate complex data into actionable insights for Customer Success, Support, Finance, and executives.
Leverage AI-assisted analytics tools and apply business intelligence best practices to ensure data quality, optimize performance, and enhance analytics capabilities.
3+ years of relevant experience in a SaaS environment.
Strong proficiency in SQL with hands-on experience using Snowflake or similar cloud data warehouse.
Proven experience developing and maintaining production-grade analytics assets and strong skills in Microsoft Power BI and/or Tableau dashboard design.
Deep understanding of SaaS KPIs such as retention, expansion, ARR, renewals, engagement, NPS, CSAT, and utilization.
Has strong analytical engineering skills combining technical expertise with business acumen to influence strategic decisions through data.
Takes ownership of analytics solutions end-to-end including development, deployment, validation, and continuous improvement while maintaining high standards of accuracy and governance.
Collaborates effectively across cross-functional teams like Data Engineering, Data Science, Customer Success, Finance, and Product to solve complex challenges and improve analytics practices.