About the Role This is a greenfield opportunity to architect and build the data platform for the agentic era — a scalable OLAP lakehouse that turns complex enterprise data into trustworthy, actionable answers. You'll join a small, high-output engineering team at an AI-native analytics company serving Fortune 100 enterprises in demanding industries like healthcare and financial services, where data quality and query performance directly drive business impact. What You'll Do Design and build core components of a greenfield OLAP lakehouse data platform from the ground up. Implement distributed data system components with a focus on join optimization and query performance. Collaborate across infrastructure, backend services, and frontend to ship end-to-end data platform features. Deliver reliable, scalable data infrastructure that supports enterprise-grade analytics at scale. What We're Looking For 4+ years of experience as a data systems, backend, infrastructure, or platform engineer building and delivering data infrastructure. Hands-on experience with OLAP lakehouse or data lakehouse architecture, including query optimization and join optimization. Proficiency in Haskell and/or TypeScript (the team's primary stack). Experience with big data systems such as Apache Spark or Hadoop . Demonstrated ability to design and implement distributed systems components. Solid experience with databases — schema design, indexing, and query execution. Strong foundation in algorithms and data structures with real-world application. Experience shipping products from zero to one in a startup or early-stage environment. Comfortable working across multiple system layers — infrastructure, services, and frontend. Prior experience at a VC-backed startup is a plus. Compensation & Benefits Base salary range: $200,000 – $350,000 USD annually, plus equity. Visa sponsorship is available. Location On-site in New York, NY . This role requires in-person presence; candidates should be based in or willing to relocate to New York City.
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