$7000 to $12000 (Monthly)
Job description:
· Expertise in GCP required.
· 4-8 years of proven software development experience with Bigdata full stack engineering.
· Collaborate with cross-functional teams to define, design, and ship new features.
· Design and build applications using Java and related technology.
· Solid hands on experience of Java/J2EE and framework such as Spring, Kubernetes, etc
· Knowledge of build tools Maven, Gradle and DevOps environment using tools such as Git (Bitbucket), Continuous Integration (Jenkins) and Continuous Deployment (Fastlane).
· Code with security and data protection.
· Experience in problem solving and root-cause analysis on any errors during the process of Software Development Life Cycle (SDLC) implementation and provide audit and compliance support when required.
· Experience in automated testing is an advantage
· Professional, adaptable and innovative with a focus on delivery
· Self-motivated team player who demonstrates initiative and flexibility
· Customer focused attitude, sensitivity to the changing and often escalated needs of the business
· Strong organizational skills, with the ability to handle and prioritize multiple tasks
· Good to have working with code quality tools such as Sonar, Fortify or NexusIQ will be advantageous.
· Tech stack: GCP,Hadoop, Spark, Hive, Java, Spring, Spring boot, Spring Webservices, Spring Cloud , Spark, Microservices, Kafka, Jenkins, git, Maven, Kubernetes, OpenShift, AWS and Linux
Responsibilities:
· Provide expert solutions in field of Big Data and cloud (AWS,GCP).GCP preferred
· Develop the security features on different data platforms with Engineering of Big Data Analytics Technology.
· Provide engineering solution and framework to support the security and access in different environments and data-driven business activities at large scale.
· Ensuring good quality and performance of product features
· Automate everything to remove the toil.
· Prepare and produce releases of software components
· Experimentation to assess new solution paths of enabling data access in various environments
· Collaborative work with remote teams.
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