About the role
About the Role
Join a fast-moving, NYC-based AI-native data infrastructure company that is building the next generation of agentic analytics. This is a greenfield opportunity to architect and build a scalable OLAP lakehouse platform that turns messy enterprise data into trustworthy, actionable answers — at scale, for some of the most data-intensive organizations in the world.
As a Senior Software Engineer on the Distributed Data Systems team, you'll own core platform components end-to-end, with a particular focus on query performance and join optimization. If you get genuinely excited about JOIN order optimization or have ever implemented a query optimizer for fun, this role was written for you.
The company is well-funded (Series A/B stage) and backed by notable strategic investors. Hiring decisions can be made within 72 hours of an onsite interview, and interview travel is covered.
Visa sponsorship is available.
What You'll Do
Work on a greenfield OLAP lakehouse project, building the data platform for the agentic era — where AI agents drive the vast majority of queries.
Design and implement distributed data system components with a strong focus on join optimization and query performance.
Collaborate fluidly across infrastructure, services, and frontend to deliver end-to-end data platform features.
Ship reliable, scalable data infrastructure that powers enterprise-grade analytics at scale.
Contribute from zero to one — this is early-stage, high-ownership work.
What We're Looking For
Required:
4+ years of experience as a data systems, backend, infrastructure, or platform engineer.
Proficiency in Haskell and/or TypeScript (the core tech stack).
Strong data focus — you think deeply about data quality, correctness, and performance.
Experience building products from zero to one; prior startup experience (ideally VC-backed) strongly preferred.
Experience with distributed systems.
Experience with big data systems (Apache Spark, Hadoop).
Experience with databases (relational, columnar, or otherwise).
Strong foundation in algorithms and data structures and their real-world applications.
Experience with OLAP lakehouse / data lakehouse architecture and query optimization.
Nice to Have:
Comfortable diving into any layer of the stack — infrastructure, services, or frontend.
Passion for building robust, scalable, and easy-to-use systems.
Background at companies working on data platforms, query engines, or AI/ML infrastructure.
Compensation & Benefits
Salary: $200,000 – $350,000 USD annually (based on experience)
Equity participation in a well-funded, high-growth startup
Interview travel covered for onsite candidates
Visa sponsorship available
Location
This role is on-site in New York, NY. Candidates should be based in NYC or willing to relocate. This is not a remote role.
Originally posted on Himalayas