Data Analyst

We're looking for a Data Analyst to help make Clay data-driven from the ground up. You'll join a team of experienced data scientists and analytics engineers, while partnering closely with Product and Go-to-Market teams to build foundational data models, dashboards, and analyses that teams rely on every day.

This role is ideal for someone earlier in their data career who wants to learn quickly from senior teammates, take on meaningful ownership from day one, and do that work inside one of the fastest-growing AI startups while digging deeply into data to understand why things are happening, not just what is happening.

- Write clean, maintainable SQL against Snowflake to power core metrics, dashboards, and analytical workflows.

- Build and iterate on metrics and tables in dbt , and surface them through dashboards in Sigma to help teams understand product usage, performance, and change over time.

- Use SQL as your primary tool, with Python or R in a notebook environment like Hex when helpful, to investigate trends, anomalies, and product behavior and connect analyses back to real business questions.

- Support reverse ETL workflows using Census , helping make modeled data actionable in the tools teams use day-to-day.

- Partner with cross-functional teams to turn ambiguous questions into clear, useful analytical outputs.

- Strong SQL fundamentals - comfortable with joins, CTEs, window functions, and clear query structure

- Experience building analytical data models or metrics tables using dbt or similar analytics-engineering workflows

- Comfortable working with BI tools like Sigma, Looker, Tableau, Mode, or similar

- Strong analytical intuition - able to ask the right questions, explore data thoughtfully, and synthesize clear, well-reasoned conclusions

- Clear communicator who can share insights with technical and non-technical partners

- Deeply curious about product usage and business performance - motivated to go beyond the what to understand the why, without getting lost in rabbit holes

- Experience with Snowflake or other similar cloud data warehousing tools

- Comfortable using SQL as the primary analysis tool, with the ability to use Python or R when helpful for deeper or more efficient analysis

- Familiarity with Hex or other notebook-based analysis tools