About this role
Job Description
Location: CHN Experience: 6-9 Years
Key Skills: Apache Airflow , Informatica , Snowflake, Azure services, Java design patterns, Data modelling, Spring boot (Spring batch framework, Hibernate ORM ,Spring security) ,
Strong Python Programming around data libraries(Pandas,Numpy), Advanced Java , powerbi,Kubernetes(AKS), Github copilot agent development experience .
Skills around Data engineering and Spring boot :
Strong proficiency in SQL and data modeling.
Experience with Spark, Kafka, Hadoop, or similar technologies.
Expertise in cloud data platforms and services.
Experience in snowflake
Knowledge of CI/CD, DevOps, and automation practices.
Understanding of data governance, security, and privacy requirements.
Strong problem-solving and analytical capabilities.
Strong proficiency in Advance Java, Spring Boot, Spring MVC, and Spring Data.
Experience with microservices architecture and event-driven systems.
Working experience around Spring batch REST APIs, OpenAPI, and API security standards.
Familiarity with Kafka, RabbitMQ, or messaging frameworks.
Experience with containerization and cloud platforms (Docker, Kubernetes, Azure/AWS).
Understanding of DevSecOps, CI/CD, and agile development methodologies.
Strong debugging, troubleshooting, and performance optimization skills.
Key Responsibilities
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Design and implement batch and real-time data ingestion pipelines.
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Build scalable ETL/ELT solutions using modern data engineering frameworks.
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Develop and optimize data models, data lakes, and data warehouse architectures.
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Ensure data quality, lineage, governance, and compliance standards.
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Optimize performance, reliability, and scalability of data processing workflows.
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Collaborate with cross-functional teams to define data requirements and solutions.
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Implement monitoring, alerting, and operational controls for data platforms.
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Support cloud-native data solutions across Azure.
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Design and develop RESTful APIs and microservices using spring and Spring Boot.
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Implement business logic and integration services for enterprise applications.
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Build scalable and resilient distributed systems using cloud-native patterns.
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Collaborate with architects, product owners, and QA teams throughout the SDLC.
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Ensure code quality through unit testing, code reviews, and automated testing.
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Optimize application performance, security, and reliability.
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Implement observability through logging, monitoring, and tracing solutions in datadoog
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Participate in CI/CD pipeline development(declarative pipeline using Jenkins core) and deployment automation.