Senior Software Engineer, Distributed Data Systems

About the Role This is a greenfield opportunity to build the data platform for the agentic era. You'll join a small, high-output engineering team at an NYC-based AI analytics startup that helps large enterprises turn messy, complex data into trustworthy, real-time answers — without writing SQL. The company is backed by strategic institutional investors and is growing fast, with a roster of large enterprise customers across finance, technology, and sports. As a Senior Software Engineer on the Distributed Data Systems team , you'll be a core contributor to a brand-new OLAP lakehouse project, working on the query engine and distributed data infrastructure that powers the next generation of agentic analytics. If you find yourself genuinely excited by JOIN order optimization or have ever built a query optimizer for fun, this role was written for you. What You'll Do Design and build components of a greenfield OLAP / data lakehouse platform from the ground up. Implement distributed data system components with a strong focus on join optimization and query performance. Contribute across the full system — infrastructure, backend services, and frontend — as needed to ship data platform features end-to-end. Ship reliable, highly scalable data infrastructure that supports enterprise-grade analytics workloads. Help shape how query behaviors evolve as AI agents increasingly drive the majority of queries. What We're Looking For Must-haves: 4+ years of hands-on experience as a data systems, backend, infrastructure, or platform engineer building or delivering data infrastructure. Demonstrated experience with OLAP lakehouse or data lakehouse architecture, including query optimization and join optimization. Proficiency in Haskell and/or TypeScript (the team's primary tech stack). Hands-on experience with big data systems such as Apache Spark or Hadoop . Proven ability to design and implement distributed systems components. Experience working with databases — schema design, indexing, and query execution. Strong foundation in algorithms and data structures with demonstrated application to real-world systems. Experience shipping products from zero to one, ideally in an early-stage or VC-backed startup environment. Nice-to-haves: Comfort working across multiple system layers — infrastructure, backend services, and frontend. Prior experience at VC-backed startups, particularly in the data/AI/ML infrastructure space. Background at companies working on query engines, distributed databases, or AI-powered analytics platforms (e.g., experience comparable to Databricks, ThoughtSpot, Hex Technologies, or similar). Location This role is on-site in New York City . Candidates should be based in or willing to relocate to NYC. Interview travel is covered, and hiring decisions move quickly — typically within 72 hours of an on-site interview. Visa sponsorship is available. Compensation & Benefits Salary: $200,000 – $350,000 USD annually, depending on experience. Early-stage equity participation. Opportunity to do some of the most technically interesting distributed systems work in the AI data space.