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Tier-1 employer, mid-level 3+ years, metro Bangalore, generalist analytics engineering increases applicant competition.
Strong SaaS metrics focus (ARR, retention) makes skills somewhat domain-specific but transferable across SaaS/product companies.
Explicit 3+ years plus mandatory Snowflake/SQL and BI production experience makes shortlisting moderately strict.
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Develop and maintain production-grade SQL models, data pipelines, and dashboards primarily using Snowflake and tools like Power BI or Tableau to support business decisions in Customer Success, Support, Finance, and executive teams.
Collaborate with Data Engineering, Data Science, and business stakeholders to define metrics, ensure data quality, automate workflows, and deliver actionable insights through rigorous quantitative analysis.
Utilize AI-assisted analytics tools and Python for data exploration, validation, automation, and quality control within a Git-based version-controlled environment following engineering best practices.
Minimum 3+ years of experience in a SaaS environment.
Strong SQL skills with hands-on experience in Snowflake or comparable cloud data warehouses.
Proven experience developing and maintaining production-grade analytics assets and dashboards using Microsoft Power BI and/or Tableau.
Work Experience Required: Minimum 3+ years in SaaS analytics roles; other specific notice period not explicitly mentioned in the JD.
Combines technical expertise in analytics engineering with strong business acumen to translate complex data into actionable strategic insights.
Experience building scalable, reusable analytics solutions with high standards of accuracy, governance, and validation of AI-assisted outputs.
Collaborates cross-functionally with Data Engineering, Data Science, Customer Success, Finance, and Product teams and takes ownership of analytics solutions from development through continuous improvement.