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Tier-1 brand, mid-level generalist title, and broad analytics skill requirements drive high competition.
Requires SaaS-specific metrics and customer-success domain knowledge, but analytics engineering skills remain transferable.
Explicit 3+ years SaaS experience and required Snowflake, SQL, and Power BI/Tableau increase shortlisting strictness.
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Develop and maintain production-grade SQL models, curated datasets, and dashboards in Snowflake and Power BI/Tableau to support retention, expansion, and growth decision-making across Customer Success and related business functions.
Partner with Data Engineering, Data Science, and business stakeholders to define reliable metrics, improve analytics capabilities, and ensure data quality and governance in analytics assets.
Translate complex data and analytical findings into clear, actionable business insights and executive-ready reports to influence strategic decisions across Customer Success, Support, Finance, and Product teams.
Minimum 3 years of relevant experience in a SaaS environment.
Strong expertise in SQL with hands-on experience using Snowflake or a comparable cloud data warehouse.
Proven experience building and maintaining production-grade analytics assets (not ad hoc reporting).
Proficient with Microsoft Power BI and/or Tableau for designing dashboards and developing reusable business metrics.
Strong analytical and technical skills focused on building scalable, maintainable analytics engineering solutions rather than only ad hoc analysis.
Demonstrates ability to validate data and AI-assisted outputs with high standards of quality, maintaining data governance practices.
Experienced collaborating cross-functionally with Data Engineering, Data Science, Customer Success, Finance, and Product teams, and capable of communicating effectively with both technical and executive stakeholders.