Backend Java Developer
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Description
Backend Java Developer – Data Fabric / Platform Engineering
Location: Pune (Hybrid)
Employment: Permanent
Experience: 4 to 8 years
If your idea of backend engineering is more than CRUD APIs and microservices boilerplate — this role is for you.
We’re building the core backend services of a Data Fabric platform that governs data access, entitlements, and query policy enforcement across distributed enterprise data systems.
This is platform engineering: deterministic rule engines, SQL planning/interception, and high-throughput services that sit on the critical path of data access.
This is deep backend + data infrastructure work.
🚀 What You’ll Do
- Build core backend services in Java (17/21) for access control and query manipulation
- Implement deterministic policy / rule engines for data governance
- Work on SQL parsing, planning, validation, and transformation (e.g., Calcite or similar planners)
- Integrate with distributed data platforms / query engines (e.g., Starburst or similar)
- Own API contracts with living documentation in CI/CD
- Build production-grade, testable pipelines
- Drive observability, reliability, and performance
- Contribute to architecture decisions (modularity, DI, extensibility)
What You Bring (Must-Have)
- Strong hands-on experience in Java (17/21) + Spring
- Deep understanding of JDBC, SQL parsing/validation, query planning/optimization
- Experience with SQL planners or query transformation layers
- Strong grounding in data structures, algorithms, and backend performance
- Production-grade testing using JUnit 5, Mockito
- Experience with clean architecture, DI, modular design
- Comfortable owning CI/CD, code quality, observability
- Familiarity with Docker, Maven, Jenkins
⭐ Nice to Have
- Apache Calcite
- Starburst or federated query engines
- JVM performance tuning
- High-throughput service interfaces (REST/gRPC)
- Data governance or policy enforcement layers
👥 This Role Is Ideal If You’ve Worked On
- Data platforms, governance layers, query engines, or SQL planners
- Backend/platform services that sit in the critical path of data access
- Systems where correctness, determinism, and performance matter
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