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Onehouse

Fully managed data lakehouse service platform

Backend Engineer - Distributed Systems

Backend EngineeringConfirmed live in the last 24 hours
Full-timeRemote in IndiaNo salary listed

About the Job

Requirements

  • At least 3 years of experience as a backend engineer, developing and operating microservices in a distributed environment.
  • Experience with Kubernetes, gRPC, and Java.
  • Experience deploying applications on one or more global cloud platforms, such as AWS, GCP, or Azure.
  • Operational excellence in monitoring, deploying, and testing microservice architectures.
  • Ability to make decisions quickly and balance feature development with technical debt.
  • Clear communication skills.

Responsibilities

  • Build highly scalable and reliable platform services to support multi-region cloud microservices.
  • Collaborate with the team to implement APIs, database and caching abstractions, and services for user-facing products, external partner integrations, or infrastructure tooling and monitoring systems.
  • Own product features through design and implementation, from concept to completion.
  • Design for future scale and high availability, understand common failure patterns, and implement remediations.
  • Maintain a high engineering bar for code, monitoring, operations, automated testing, and platform release management.

Desired Qualifications

  • Experience with Go.
  • Experience with Firebase or an equivalent database.
  • Experience working on a SaaS product.

About the Company

Onehouse

Fully managed data lakehouse service platform

Onehouse provides a fully managed data lakehouse on open storage that supports multiple table formats like Apache Hudi, Iceberg, and Delta Lake. It works by letting customers specify the data to organize and optimize, while the service automatically handles data management tasks such as clustering, compaction, masking, encryption, and change data capture, deployable in minutes. It differentiates itself with open-storage lakehouse principles, format flexibility, automated optimization, security features, and a pay-as-you-go model that lowers data-management costs. The goal is to make data management simpler and cheaper while enabling fast access for BI, real-time analytics, and AI/ML workloads.

Company size
51-200
Company stage
Series B
Total funding
$68M
Headquarters
Sunnyvale, CA
Founded
2021

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