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Mid-level generalist role, metro Bangalore, strong company brand, and broad in-demand skills increase applicant competition.
Analytics engineering skills are transferable, but SaaS-specific KPIs and product data add moderate industry specificity.
Explicit three-plus years, mandatory Snowflake/SQL and BI production experience enforce strict technical filtering.
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Develop and maintain production-grade SQL models, data pipelines, and dashboards using Snowflake, Power BI, and Tableau to support retention, expansion, and growth decisions.
Partner with Data Engineering, Data Science, and business stakeholders to define reliable metrics and deliver actionable insights across Customer Success, Support, Finance, and executive teams.
Use AI-assisted analytics tools and Python for analysis, automation, and quality control while ensuring data and metric quality with engineering best practices in a Git-controlled environment.
3+ years of relevant experience in a SaaS environment.
Strong SQL skills with hands-on experience in Snowflake or comparable cloud data warehouse.
Proven experience building and maintaining production-grade analytics assets, not just ad hoc reports.
Strong experience with Microsoft Power BI and/or Tableau, including dashboard design and trusted metric development.
Technical expertise in scalable analytics engineering combined with strong SaaS business acumen including retention, ARR, renewals, and customer satisfaction metrics.
Ability to translate complex data into clear, actionable insights and influence strategic decisions across cross-functional teams including Customer Success and Finance.
Experience validating AI-assisted outputs and applying rigorous quality governance while continuously improving analytics solutions and engineering practices.