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Mid-level analytics role at a well-known SaaS with common BI/SQL skills draws moderate applicant competition.
Role requires SaaS GTM and RevOps domain knowledge, moderately reducing cross-industry transferability.
Explicit 5–8 years requirement plus mandatory SQL, warehouse, and SaaS GTM experience enforces strict filters.
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Own the data strategy and analytics powering global Sales operations, including pipeline health, forecasting, and sales planning (capacity, quota, territory, headcount).
Develop and maintain AI-driven analytical models and reusable skills for sales pipeline and capacity planning, integrating data from multiple sources like Salesforce, Gong, and Netsuite.
Partner cross-functionally with Sales leadership, RevOps, Marketing, and Finance to deliver standardized metrics, dashboards, and training to drive data-informed decision-making and adoption of AI analytics tools.
5–8+ years experience in Data Analytics, Analytics Engineering, or BI roles.
Advanced SQL proficiency and experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift.
Strong background in SaaS sales metrics (ARR, pipeline generation, quota attainment, forecast accuracy) and hands-on experience with BI/planning tools (Pigment, Looker, Tableau, Power BI, or Mode).
Experience supporting enterprise Sales/RevOps teams including go-to-market planning.
Experienced at bridging analytics, data engineering, and business strategy in complex sales environments, especially enterprise SaaS sales operations.
Skilled in building scalable, version-controlled analytical pipelines and AI-native analytics components (skills-as-code, LLM-assisted analysis) with emphasis on governance and data quality.
Able to drive adoption of data and AI analytics across sales teams, producing trusted metrics and actionable insights embedded in operational workflows.