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
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Design and build core components of a greenfield OLAP lakehouse data platform from the ground up.
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Implement distributed data system components with a focus on join optimization and query performance.
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Collaborate across infrastructure, backend services, and frontend to ship end-to-end data platform features.
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Deliver reliable, scalable data infrastructure that supports enterprise-grade analytics at scale.
What We're Looking For
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4+ years of experience as a data systems, backend, infrastructure, or platform engineer building and delivering data infrastructure.
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Hands-on experience with OLAP lakehouse or data lakehouse architecture, including query optimization and join optimization.
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Proficiency in Haskell and/or TypeScript (the team's primary stack).
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Experience with big data systems such as Apache Spark or Hadoop.
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Demonstrated ability to design and implement distributed systems components.
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Solid experience with databases — schema design, indexing, and query execution.
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Strong foundation in algorithms and data structures with real-world application.
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Experience shipping products from zero to one in a startup or early-stage environment.
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Comfortable working across multiple system layers — infrastructure, services, and frontend.
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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.