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Tier-1 brand, mid-level generalist analytics role with common tooling and 3+ years requirement drives high competition.
Requires SaaS domain knowledge and customer-success metrics, limiting cross-industry transferability.
Explicit 3+ years SaaS experience and mandatory production-grade Snowflake, SQL, and BI deliverables impose medium strictness.
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Develop and maintain production-grade SQL models, data pipelines, and interactive dashboards using Snowflake, Power BI, and Tableau to drive retention, expansion, and growth decisions.
Partner across Data Engineering, Data Science, and business teams to define, validate, and maintain reliable metrics and analytical assets supporting Customer Success, Support, Finance, and executive leadership.
Leverage AI-assisted analytics tools and Python for data exploration, quality control, automation, and translating complex data into actionable business insights.
Minimum 3 years of experience in a SaaS environment with understanding of SaaS KPIs such as retention, expansion, ARR, renewals, NPS, CSAT, and utilization.
Strong SQL skills with hands-on experience using Snowflake or similar cloud data warehouses; proven production-grade analytics asset development experience.
Proficient in Microsoft Power BI and/or Tableau for designing dashboards and reusable business metrics.
Work Experience Required: Minimum 3 years in SaaS analytics or related fields.
Experienced analytical engineer combining strong technical SQL and dashboarding skills with business acumen to influence strategic decisions in SaaS contexts.
Demonstrates deep ownership by building scalable, maintainable analytics solutions with high standards for data accuracy, governance, and AI-validated outputs.
Collaborates effectively across cross-functional teams (Data Engineering, Data Science, Customer Success, Finance) and communicates complex insights clearly to both technical and senior business stakeholders.