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Camunda

Software Engineer, Backend - Data Layer

Remote (Remote)fulltimemidAdded today

About this role

Camunda seeks a Backend Software Engineer to design and maintain the data layer powering Camunda 8, handling storage and querying of process data across relational databases and Elasticsearch/OpenSearch. You'll own end-to-end delivery of data infrastructure initiatives, optimize performance at scale, and support production operations.

What you'll do

  • Design and build backend services for the data layer storing and serving process data across relational and search systems
  • Own full delivery of engineering initiatives from requirements to high-quality deployment, collaborating with product and senior engineers
  • Optimize how process data is processed, retained, and exposed to meet diverse customer needs
  • Enhance secondary storage system performance and scalability, and build operational tooling for troubleshooting
  • Participate in L3 support rotations and on-call shifts, investigating production data layer issues
  • Partner with Product, QA, Design, and Support teams to influence data layer evolution

What they're looking for

  • Backend systems design and development
  • PostgreSQL, MySQL, MariaDB, MSSQL, or equivalent relational database expertise
  • Elasticsearch/OpenSearch administration and optimization
  • Query performance tuning and indexing strategies
  • Data modeling and schema design
  • Production systems troubleshooting and debugging
  • Distributed systems understanding
  • Java or similar backend programming language
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Camunda

Camunda builds business process automation and CI/CD infrastructure platforms, with emerging focus on AI-powered process orchestration through products like ProcessOS. The company is hiring Software Engineers for infrastructure scaling and Forward Deployed Engineers to drive enterprise customer deployments across Java and React tech stacks.

Website
camunda.com
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Likely interview questions

  • Describe your experience optimizing database query performance in a high-scale production environment—what were the bottlenecks and how did you resolve them?
  • How have you approached designing a data layer that balances between relational and search-based storage systems?
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