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Senior Software Engineer, Distributed Data Systems

Key Facts

Remote From: 
Full time
Senior (5-10 years)
200 - 350K yearly
English

Other Skills

  • Collaboration
  • Reliability

Roles & Responsibilities

  • 4+ years of experience as a data systems, backend, infrastructure, or platform engineer
  • Proficiency in Haskell and/or TypeScript
  • Experience building products from zero to one; prior startup experience preferred
  • Experience with distributed systems

Requirements:

  • Work on a greenfield OLAP lakehouse project, building the data platform for the agentic era
  • Design and implement distributed data system components with a 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

Job description

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.

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