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About the Role

This is a rare greenfield opportunity to build the data platform for the agentic era. You'll join a small, high-output engineering team at a fast-moving NYC-based AI data analytics startup, working on a brand-new OLAP lakehouse project designed to turn messy enterprise data into trustworthy, real-time answers at scale. As query behavior shifts to be driven largely by AI agents, the architecture of the underlying data platform matters more than ever. If you get genuinely excited about JOIN order optimization or have implemented a query optimizer for fun, this role was written for you. Visa sponsorship is available.

Responsibilities

Design and implement core components of a greenfield distributed OLAP lakehouse platform.
Focus deeply on join optimization, query planning, and query performance at scale.
Build reliable, scalable data infrastructure to support enterprise-grade analytics workloads.
Collaborate across infrastructure, backend services, and frontend as needed to ship end-to-end platform features.
Take ownership of zero-to-one product work in a fast-paced early-stage environment.

Requirements

4+ years of experience as a data systems, backend, infrastructure, or platform engineer.
Hands-on experience with distributed systems.
Experience working with databases (relational and/or analytical).
Strong foundation in algorithms and data structures and their real-world applications.
Experience at an early-stage, VC-backed startup.
Comfort diving into any layer of the stack — infrastructure, services, or frontend.

Skills

Haskell
TypeScript
Data correctness
Data performance
Data reliability
Building products from zero to one
Big data systems (Apache Spark, Hadoop)
OLAP lakehouse / data lakehouse architecture
Query optimization

Location

New York City, NY

Work Type

On-site
Full-time

Experience Level

4+ years

Salary/Compensations

$200,000 – $350,000 USD annually

Benefits

Equity participation in a well-funded, early-stage company.
Interview travel covered.
Hiring decisions made quickly (within ~72 hours of on-site interviews).

About the Company

NYC-based AI data analytics startup.