Analyst/Senior Analyst, Analytics
Listed on 2026-04-29
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IT/Tech
Data Analyst, Business Systems/ Tech Analyst, Data Science Manager
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI‑native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high‑trust collaborator that is core to how you solve problems and accelerate your impact.
We look for low‑ego individuals who thrive in dynamic and fast‑moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn’t just to execute a function, but to help redefine the future of how work gets done.
You’ll be central to how we bring AI to the People and Legal functions ng Snowflake Cortex and other tools, you’ll design and deliver conversational analytics experiences — skills that let HR and Legal users ask questions in natural language and get immediate, data‑grounded answers. This means owning the full stack: the data layer that powers the AI, the logic that shapes what it knows, and the quality bar that makes it trustworthy.
Co‑ownthe data foundations with Analytics Engineering
You’ll work hand‑in‑hand with the Analytics Engineering team to design, build, and evolve the Snowflake data layer that every AI experience depends on. That means jointly scoping data models, translating stakeholder requirements into engineering work, validating that outputs are accurate, and ensuring the right access controls are in place. The AI is only as good as the foundation beneath it — and you’ll share ownership of getting that right.
Translatestakeholder needs into working products
Partner directly with Talent Acquisition, HR Business Partners, Compensation, Legal Operations, and employment counsel to understand what questions they’re trying to answer. You’ll turn those conversations into structured data models, AI skill definitions, and — where needed — dashboards that give teams something they can use immediately.
Deliver actionable insightsYou’ll work with People and Legal stakeholders to surface findings that actually change decisions — whether that’s flagging attrition risk in a business unit, identifying bottlenecks in the hiring funnel, or surfacing spend trends for legal leadership. The measure of success isn’t a dashboard going live, it’s a stakeholder doing something different because of what you showed them.
Maintain rigor as we scaleAI experiences break in quiet ways when the data drifts. You’ll own testing, validation, and quality checks across the products you build — making sure outputs stay aligned with source systems, business definitions hold, and stakeholders can trust what they’re seeing.
Contribute to access and security designHelp design and maintain the role‑based access model for sensitive HR and Legal data — including secure views, row‑level policies, and data sensitivity controls that ensure the right people see the right data.
What We’re Looking For- 3+ years of experience in analytics, data engineering, or a related field where you’ve owned data products end to end
- Strong SQL — you write complex queries and think carefully about performance, grain, and correctness
- Familiarity with the modern data stack: tools like dbt, Airflow, and Git as part of a collaborative engineering workflow
- Experience working directly with non‑technical stakeholders — you can translate a business question into a working data model and explain your thinking without jargon
- Data quality instincts — you validate your work against source systems and don’t ship without checking your numbers
- Curiosity about AI and where it’s going — you don’t need to have shipped an LLM product, but you should be excited about building them
- Hands‑on experience with Snowflake Cortex, LLM‑powered analytics tools, or building conversational data experiences
- Familiarity with Streamlit for building lightweight internal apps and dashboards
- Background in people analytics — workforce planning, attrition, compensation, or talent acquisition
- Exposure to Legal Operations data —…
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