Sr Application Architect - Hadoop Administrator

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Job Summary

This position is responsible for ensuring alignment of project specific designs with application architecture roadmap; supporting project and/or product teams on functional and technical design activities; defining the interaction between application packages, databases, and middleware systems to optimize product functional coverage; acting as subject matter expert (SME) for products that require integration into the application.Required Job Qualifications:

• Bachelor degree and 5 years Information Technology experience OR Technical Certification and/or College Courses and 7 year Information Technology experience OR 9 years Information Technology experience.
• Experience in application and/or product feature design.
• Experience in application configuration
• Experience in application development platforms and/or languages (HTML/CSS/Java/ASP.Net/PHCSC/Ruby/C#).
• Experience in cloud computing (SaaS / PaaS).
• Experience in DevOps and/or continuous deployment and/or integration process and tools (Bamboo, jenkins, RallyDev, Jira).
• Experience in integration technologies ( Tibco/Informatica/CAS).
• Experience in iterative and/or agile and/or scrum development.
• Experience in solution architecture.
• Application domain knowledge.
• Prototyping.
• Problem solving / analytical thinking.
• Teamwork and collaboration.

Preferred Job Qualifications:

• Linux/Unix Proficiency: Deep understanding of Linux OS, command-line operations, file systems, process management, and shell scripting (Bash/Perl), as Hadoop primarily runs on Linux
• Core Hadoop Ecosystem: Practical knowledge of Hadoop architecture including HDFS (Hadoop Distributed File System) for storage, YARN for resource management, and MapReduce
• Cluster Management & Monitoring: Experience with tools like Apache Ambari Nagios, Ganglia, or enterprise distributions like Cloudera Manager to track cluster health
• Ecosystem Tools: Familiarity with supporting data tools commonly integrated with Hadoop, such as Hive, HBase, Spark, and Sqoop
• Cluster Management & Schedulers: Familiarity with cluster coordination/job flows through tools like Zoo Keeper or Oozie.
• Networking & Hardware Basics: Understanding of CPU, memory, storage configurations, and network bottlenecks in distributed node environments