As an Analytics Engineer at Tavily, you’ll turn messy, complex data into clear, actionable insight. You’ll build clean, well-modeled datasets, design core business metrics, and help teams across the company make better decisions, faster.
This is a great role for someone who loves digging into ambiguity, asking sharp questions, and building clarity through data.
What You’ll Do:
Own the transformation layer of the data stack using dbt and SQL
Design and maintain core data models and business logic
Build dashboards and reports with BI tools.
Work directly with teams across product, buisness, and R&D to surface insights.
Tame messy, multi-source data (Snowflake, MongoDB, other NoSQL/SQL systems).
What We’re Looking For:
2–5 years in an analytics, data, or BI role
Strong SQL skills and experience with dbt or equivalent frameworks
Proficent in Python for data analysis and automation (pandas , plotly...)
Experience with BI tools and building user-friendly dashboards
Strong business understanding, you don’t just write queries, you ask why
Love for messy data and a track record of turning it into something useful
Experience with Snowflake and MongoDB (or similar)
Nice to Have:
Experience in a fast-paced startup
Familiarity with Airflow or other orchestration tools
Background in experimentation or A/B testing
We’re looking for someone who’s part analyst, part engineer, and all about impact.
Top Skills
What We Do
Search. Extract. Crawl. The web access stack built for builders, by builders.
Tavily powers the next generation of agents with a suite of tools for real-time Search, structured data Extraction, and fully-rendered Crawling — everything agents need to access and reason over the live web.
Purpose-built for RAG, autonomy, and production-grade agent systems.
