India · Mid Level
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| Job Purpose | We are looking for a Data Engineer with 3–6 years of experience with strong hands-on in cloud, data engineering, event streaming, software development, and emerging AI-assisted engineering practices to build and support scalable real-time data platforms. |
| Duties and Responsibilities | • Event Streaming: Apache Kafka, Azure Event Hubs event processing. • Azure Cloud: Azure Storage, Cosmos DB, App Service, Functions, Key Vault • Data Engineering: Databricks, Apache Spark/PySpark, ETL/ELT pipelines, data transformation and data integration. • Databases: SQL Server, NoSQL databases such as Cosmos DB/MongoDB, and Time-Series databases like Kusto / clickhouse. • Programming: .NET Core / C#, Python, REST APIs and JSON. • Containers & Kubernetes: Docker, AKS (Azure Kubernetes Service), ACR (Azure Container Registry) and containerized application deployment is must. • DevOps & CI/CD: Azure DevOps, Git, CI/CD pipelines, build/release automation and deployment management. • Architecture: Knowledge of Distributed systems, microservices, event-driven architecture and cloud-native applications. • AI-Assisted Engineering: Exposure to GitHub Copilot / GitHub Agent, AI-assisted coding, code generation, debugging, test generation and developer productivity tools is a plus. • AI & Data Engineering: Understanding of Generative AI, LLMs, AI agents, RAG, vector databases and AI-enabled data applications is an advantage. |
| Required Qualifications and Experience | • 3–6 years of relevant experience in Data Engineering / Software Engineering. • Strong SQL and programming fundamentals. • Hands-on experience with Azure cloud technologies. • Practical experience with event streaming and real-time data processing. • Experience with CI/CD and DevOps practices. • Good understanding of NoSQL and distributed data systems. • Exposure to AI-assisted software development and modern developer productivity tools is preferred. • Strong analytical, debugging and problem-solving skills. • Ability to work with high-volume, scalable and production-grade data platforms. Primary Technology Stack Azure | Kafka / Event Hubs | Databricks | NoSQL | Time-Series DB | .NET Core | C# | Python | AKS | ACR | Docker | Azure DevOps | CI/CD | SQL | GitHub Copilot / Agent | GenAI |
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