SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Exa is an applied AI lab building a next-generation search engine powered by massive-scale infrastructure, state-of-the-art embedding models, and high-performance vector databases. The company powers search for Cursor, Cognition, HubSpot, and over 400,000 developers, with $350M in funding from Lightspeed, Benchmark, and a16z.
As an Analytics Engineer, you'll sit at the intersection of analytics, data science, and data engineering, building internal data products that drive decision-making across the entire organization. You'll have significant autonomy in leading analytics initiatives and designing the data pipelines that power them.
Key responsibilities include:
- Designing and maintaining canonical datasets that serve as single sources of truth for company-wide metrics
- Building end-to-end data pipelines to analyze petabytes of web search data
- Scaling analytics across the company by creating data products, self-serve tools, and internal BI solutions for product, finance, marketing, and GTM teams
- Developing quantitative models for forecasting and experimentation
- Owning the A/B testing infrastructure used to validate product and business hypotheses
You'll need strong proficiency in Python, SQL, and cloud-based data processing, warehousing, and orchestration platforms. The ideal candidate is obsessively detail-oriented about establishing accurate metrics with analytical rigor, proactive about championing data-driven decision-making and data integrity, and enthusiastic about statistical methods, time-series forecasting, experimental design, and hypothesis testing. Experience with database internals, reliable ETL/ELT pipeline construction, and query/system optimization for performance and cost is expected.
