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Staff Software Engineer- Backend

Acceldata· Engineering – R&D (Dev)
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BengaluruFull-timePosted 6mo ago

About the role

Acceldata is reimagining how companies observe their data with a data observability platform. This role focuses on designing and building scalable backend systems and microservices using Java.

Responsibilities

  • Design and build scalable, reliable, and performant distributed systems using Java and microservices architecture.
  • Contribute to system design discussions, architecture reviews, and technical decisions.
  • Develop robust APIs and microservices with high availability and low latency.
  • Collaborate with cross-functional teams (Product, Data, DevOps) to deliver high-quality releases.
  • Optimize system performance and scalability across large datasets.
  • Mentor junior engineers and contribute to engineering best practices.

Qualifications

  • 9–12 years of hands-on experience in backend development using Java.
  • Strong understanding of distributed systems, system design, and microservices.
  • Experience with NoSQL databases (e.g., Cassandra, MongoDB, DynamoDB).
  • Hands-on experience with event streaming technologies (e.g., Kafka, Spark).
  • Solid experience in building large-scale, cloud-native systems.
  • Working knowledge of Databricks or Snowflake or Big Data technologies is preferred.
  • Excellent problem-solving, debugging, and analytical skills.
  • Strong ownership and ability to work in a fast-paced product environment.

Skills

Required:JavaDistributed systemsMicroservicesNoSQL databasesEvent streaming

Benefits

  • Mentorship & Growth
  • ESOPs
  • Medical and Life Insurance
  • Paid Maternity & Parental Leave
  • Corporate Uber Program
  • Learning & Development Support
Last updated Oct 22, 2026. Interested? Apply on the company site.

About Acceldata

AI-Native Data Management for the Modern Enterprise

Discover Acceldata, the industry’s first agentic data management platform, revolutionizing data observability, governance, optimization, and AI-driven operations. Enhance data reliability, reduce costs, and maximize efficiency across hybrid environments.

Data ObservabilityData ManagementAI-driven OperationsHybrid Environments
Company profileWebsite

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