Senior Software Engineer, Distributed Data Systems

Clera

$200K — $350K *
Enterprise 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.
  • Strong focus on data correctness, performance, and reliability.
  • Experience in building products from zero to one in a startup environment.
  • Hands-on experience with distributed systems.
  • Familiar with big data systems like Apache Spark and/or Hadoop.
  • Background in relational and/or analytical databases.
  • Knowledge of OLAP lakehouse architecture and query optimization.

Responsibilities

  • Design and implement core components of a distributed OLAP lakehouse platform.
  • Optimize joins, plan queries, and enhance query performance at scale.
  • Build reliable, scalable data infrastructure for enterprise analytics workloads.
  • Collaborate across services to deliver end-to-end platform features.
  • Own zero-to-one product work in a fast-paced startup.

Benefits

  • Equity participation in a well-funded early-stage company.
  • Interview travel expenses covered.
  • Quick hiring decisions within ~72 hours of on-site 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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