Data Platform Developer

2 days ago

Pune, Maharashtra, India beBeeData Full time ₹ 1,21,90,000 - ₹ 2,13,70,000

As a seasoned Solutions Architect, you will play a pivotal role in designing, building, and maintaining enterprise-grade data platforms. This position requires expertise in distributed systems, real-time data integration, metadata-driven design, and cloud-native development.

You will collaborate with cross-functional teams to implement scalable, secure, and well-governed systems while working closely with engineering, data, and governance stakeholders.

Main Responsibilities

  • Design and develop platform-level components, including metadata management, data integration, and semantic modeling
  • Develop and maintain reliable, scalable, and observable services supporting operational and analytical workloads
  • Contribute to the design and development of real-time data pipelines, schema evolution strategies, and lineage tracking mechanisms
  • Participate in architectural reviews, POCs, and production rollouts for key platform capabilities
  • Implement and optimize APIs, orchestration patterns, and data services for internal and external consumers
  • Deliver features from design to deployment, ensuring alignment with technical standards and business needs
  • Troubleshoot performance bottlenecks, integration issues, and infrastructure gaps with DevOps and architecture teams
  • Document engineering components, workflows, and dependencies following architecture and compliance guidelines

Requirements

  • 10+ years of hands-on experience in backend, data, or platform engineering, preferably in cloud-native environments
  • Strong knowledge of distributed systems, microservices, and scalable data architecture
  • Experience implementing real-time data ingestion, streaming pipelines, and event-driven architectures
  • Proficient in Python, Java/Scala, and SQL for building high-performance data services and APIs
  • Integrate with REST, GraphQL, and gRPC APIs across multiple services
  • Familiarity with Kubernetes, GitOps, and infrastructure-as-code tools
  • Understanding of metadata management, data lineage, and semantic models
  • Data governance practices, including access control, quality rules, and auditability
  • Certifications in Cloud platforms, Kubernetes, or Data Engineering preferred

Preferred Qualifications

  • Experience working in federated data platforms, data mesh, or knowledge graph environments
  • Understanding of multi-cloud architectures and cloud-native best practices

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