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Mid-level generalist data role with 3–5 years and broad skillset increases candidate competition.
Core analytics and SQL transferable, but SaaS metric fluency and daily LLM workflows increase domain specificity.
Multiple mandatory technical skills, explicit years, and required daily LLM workflows make shortlisting strict.
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Own the correctness and definition of core metrics, data models, and AI answer layer for the internal analytics platform.
Investigate metric changes, automate repetitive analysis using AI agents, and ensure data quality with early error detection.
Work cross-functionally with Revenue, Customer Success, Finance, and Executive teams to explain findings and handle sensitive data access properly.
3–5 years experience in data analytics, analytics engineering, or applied data science in a product or SaaS company.
Strong SQL skills including CTEs, window functions, complex joins, and performance tuning on large tables.
Proficient in data modeling concepts such as grain, star schemas, and slowly changing dimensions; experience with cloud data warehouses (Snowflake preferred).
Daily practical use of large language models (LLMs) with at least one automated workflow implemented using AI tools.
Experienced in applying deep data modeling and advanced SQL to support product or SaaS business metrics.
Comfortable integrating AI tools into workflows and automating data analysis rather than occasional AI usage.
Capable of working across multiple teams with strong attention to detail and clear communication to non-technical stakeholders.