Analytics Engineer
Exa is an applied AI lab building a search engine unlike the world has ever seen. We build massive-scale infra to crawl the entire web, train state-of-the-art embedding models to process it, and design super high performant vector databases to retrieve over it. We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised $350m from Lightspeed, Benchmark, and a16z.
Our ultimate goal is to build perfect search over all the world's information, far beyond Google. If you want to build massive-scale ML systems that will define the way the new AI world consumes information, this is the place for you.
This role sits at the intersection of analytics, data science, and data engineering. As an Analytics Engineer, you’ll build internal data products that influence decision-making across the whole company. You'll have enormous autonomy in leading analytics projects, as well as designing and maintaining the data pipelines that power them.
Who you are
Strong proficiency in Python, SQL, and cloud services for data processing, warehousing, and orchestration.
Obsessively detail-oriented over establishing accurate metrics with analytical rigor.
A proactive cross-functional champion for data-driven decision-making, data integrity, and rigorous data requirements grounded in business needs.
Enthusiast about statistical methods, time-series forecasting, experimental design, and hypothesis testing.
Familiarity with database internals and building reliable ETL/ELT pipelines.
Experience optimizing queries and data systems for performance and cost.
What you could do
Design and maintain canonical datasets that serve as sources of truth for metrics across the entire company.
Build end-to-end data pipelines for analyzing petabytes of web search data.
Scale analytics across the company by building data products, self-serve tools, and internal BI tools for product, finance, marketing, and GTM teams.
Develop quantitative models that form the basis for our forecasting and experimentation.
Own the A/B testing infrastructure used to test hypotheses about our product and business.
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