Who you are
- 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
- Exposure to Legal Operations data — matter management, legal spend, or outside counsel analytics
- Python experience for data pipelines, scripting, or automating reporting workflows
- Experience designing access controls for sensitive data: privileged legal information and confidential business data
What the job involves
- You'll be central to how we bring AI to the Legal function at Snowflake.
Using Snowflake
Cortex and other tools, you'll design and deliver conversational analytics experiences — skills that let 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
- 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
- Partner directly with 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
- You'll work with Legal stakeholders to surface findings that actually change decisions -- whether that's giving the GC visibility into outside counsel spend vs. budget, flagging contracts approaching expiration without a renewal signal, or helping practice area leads understand where task backlogs are building and which teams are generating the most legal work.
- The measure of success isn't a dashboard going live, it's a stakeholder doing something different because of what you showed them
- AI 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
- Help design and maintain the role-based access model for sensitive and privileged Legal data — including secure views, row-level policies, and data sensitivity controls that ensure the right people see the right data. Legal data carries unique confidentiality obligations and you'll help make sure the architecture reflects that
Benefits
- Comprehensive health insurance plans
- Life and disability insurance
- Weekly online lunch and learns
- Ergonomic work-from-home equipment
- On-demand mental health and wellness programs
- Fertility benefits and family planning resources
- Generous time-off and various leave plans
- Employee discounts and pre-tax selections
- New hire equity + Employee Stock Purchase Plan (ESPP)
- Quarterly bonus or commission program