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:
Design and implement batch and real-time data ingestion pipelines.
Build scalable ETL/ELT solutions using modern data engineering frameworks.
Develop and optimize data models, data lakes, and data warehouse architectures.
Ensure data quality, lineage, governance, and compliance standards.
Optimize performance, reliability, and scalability of data processing workflows.
Collaborate with cross-functional teams to define data requirements and solutions.
Implement monitoring, alerting, and operational controls for data platforms.
Support cloud-native data solutions across Azure.
Design and develop RESTful APIs and microservices using spring and Spring Boot.
Implement business logic and integration services for enterprise applications.
Build scalable and resilient distributed systems using cloud-native patterns.
Collaborate with architects, product owners, and QA teams throughout the SDLC.
Ensure code quality through unit testing, code reviews, and automated testing.
Optimize application performance, security, and reliability.
Implement observability through logging, monitoring, and tracing solutions in datadoog
Participate in CI/CD pipeline development(declarative pipeline using Jenkins core) and deployment automation.
