Senior Software Engineer, Distributed Data Systems
Clera New York, New York, United States · $200K–$350K/yr
Technology, Information and Internet · 2-10 employees
About the role
Design and build core components of a greenfield distributed OLAP lakehouse platform from the ground up. Drive query performance improvements and collaborate across infrastructure, backend, and frontend layers to deliver end-to-end data platform features.
What they look for
Requirements
Requires 4+ years of experience in data systems or backend engineering with hands-on experience in OLAP lakehouse architecture. Proficiency in Haskell or TypeScript and experience building distributed data systems are essential.
Benefits
Full description
About the Role
This is a Senior Software Engineer, Distributed Data Systems role at a seed-stage AI-native enterprise analytics startup based in New York City. The company is building an agentic data lakehouse — a next-generation data platform designed to turn messy enterprise data into trustworthy, queryable answers at scale. Backed by notable institutional investors and serving large-scale enterprise customers across healthcare, financial services, and Fortune 100 companies, the team is roughly 40 people and growing fast.
You'll join at a pivotal moment to work on a greenfield OLAP lakehouse project — building foundational data infrastructure for the agentic era, where autonomous agents will drive the vast majority of queries. If you find yourself genuinely excited by JOIN order optimization or have ever implemented a query optimizer for fun, this role was written for you.
Visa sponsorship is available.
What You'll Do
- Design and build core components of a greenfield distributed OLAP lakehouse platform from the ground up.
- Drive query performance improvements, including join optimization and query execution strategies suited to agent-driven workloads.
- Collaborate across infrastructure, backend services, and frontend layers to deliver end-to-end data platform features.
- Ship reliable, scalable data infrastructure that supports enterprise-grade analytics at scale.
- Contribute to zero-to-one product development in a fast-moving, early-stage environment.
What We're Looking For
Required:
- 4+ years of experience as a data systems, backend, infrastructure, or platform engineer with a focus on building or delivering data infrastructure.
- Hands-on 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).
- Experience building and shipping distributed data systems or big data platforms (e.g., Apache Spark, Hadoop).
- Demonstrated experience designing and implementing distributed systems components.
- Experience working with databases — including schema design, indexing, and query execution.
- Strong foundation in algorithms and data structures with real-world application.
- Experience shipping products from zero to one in a startup or early-stage environment, ideally VC-backed.
Nice to Have:
- Comfort working across multiple system layers: infrastructure, backend services, and frontend.
- Prior experience at a VC-backed startup.
- Background at companies operating in AI/ML, data engineering, or analytics infrastructure (e.g., companies like Databricks, ThoughtSpot, Hex, or similar).
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 onsite interviews).
Location
This role is on-site in New York City. Candidates should be based in NYC or willing to relocate. Remote work is not available for this position.
