Senior Software Engineer, Distributed Data Systems

Clera

$200K — $350K *
US-AnywhereRemote in New York, NY
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years in data systems, backend, infrastructure, or platform engineering.
  • Proficient in Haskell and/or TypeScript for core tech development.
  • Strong focus on data correctness, performance, and reliability.
  • Experience building products from scratch, preferably in a startup environment.
  • Hands-on experience with distributed systems is essential.
  • Familiarity with big data technologies like Apache Spark and Hadoop.
  • Knowledge of relational and analytical databases; strong algorithm and data structure skills.
  • Experience with OLAP lakehouse architecture and query optimization.

Responsibilities

  • Design and implement core components of a new distributed OLAP lakehouse platform.
  • Optimize join operations and enhance query planning and performance at scale.
  • Build reliable data infrastructure for enterprise-grade analytics.
  • Collaborate with infrastructure and backend teams to deliver end-to-end platform features.
  • Own projects from inception to implementation in a startup setting.

Benefits

  • Equity participation in a well-funded, early-stage company.
  • Travel expenses for interviews are covered.
  • Quick hiring decisions typically made within 72 hours after interviews.
Full Job Description
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 for this role.
What You'll Do
  • 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.
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 team's core tech stack).
  • Strong data focus - you think deeply about data correctness, performance, and reliability.
  • Experience building products from zero to one, ideally in a startup environment.
  • Hands-on experience with distributed systems.
  • Experience with big data systems such as Apache Spark and/or Hadoop.
  • Experience working with databases (relational and/or analytical).
  • 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:
  • Comfort diving into any layer of the stack - infrastructure, services, or frontend.
  • Experience at an early-stage, VC-backed startup.
Compensation & Benefits
  • Salary: $200,000 - $350,000 USD annually, depending on experience.
  • Equity participation in a well-funded, early-stage company.
  • Interview travel covered; hiring decisions made quickly (within ~72 hours of on-site interviews).
Location

This role is on-site in New York City, NY. Candidates should be NYC-based or willing to relocate. This is not a remote role.

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