Hadoop Engineer SME (Chicago, CLT)

Description

Hadoop Engineer (SME) role supporting NextGen Platforms built around Big Data Technologies (Hadoop, Spark, Kafka, Impala, HBase, Docker-Container, Ansible and many more). Requires experience in cluster management of vendor-based Hadoop and Data Science (AI/ML) products like Cloudera, Databricks. Hadoop Engineer is involved in the full life cycle of an application and part of an agile development process. They require the ability to interact, develop, engineer, and communicate collaboratively at the highest technical levels with clients, development teams, vendors, and other partners. The following section is intended to serve as a general guideline for each relative dimension of project complexity, responsibility, and education/experience within this role.

• Works on complex, major or highly visible tasks in support of multiple projects that require multiple areas of expertise
• Team member will be expected to provide subject matter expertise in managing Hadoop and Data Science Platform operations with focus around Cloudera Hadoop, Jupyter Notebook, OpenShift, Docker-Container Cluster Management and Administration
• Integrates solutions with other applications and platforms outside the framework
• He / She will be responsible for managing platform operations across all environments which includes upgrades, bug fixes, deployments, metrics / monitoring for resolution and forecasting, disaster recovery, incident / problem / capacity management
• Serves as a liaison between client partners and vendors in coordination with project managers to provide technical solutions that address user needs

Experience on L1, L2 L3 level support in Hadoop Platform

Experience in Yarn , Spark and Impala job debugging and troubleshooting

Experience in addressing issues around Name node , HDFS Space , File/Folder Permission backups

Understanding and experience in experience in query performance tuning and resource utilization tuning

Technical knowledge on relational databases, data warehousing and SQL skills

Hadoop, Kafka, Spark, Impala, Hive, HBase, Ozone etc.

Strong knowledge of Hadoop Architecture, HDFS, Hadoop Cluster and Hadoop Administrator's role

Intimate knowledge of fully integrated AD/Kerberos authentication

Experience setting up optimum cluster configurations

Debugging knowledge of YARN.

Hands-on with analyzing various Hadoop log files, compression, encoding, file formats

Expert level knowledge of Cloudera Hadoop components such as HDFS, Sentry, HBase, Kafka, Impala, SOLR, Hue, Spark, Hive, YARN, Zookeeper and Postgres

Strong technical knowledge: Unix/Linux; Database (Sybase/SQL/Oracle), Java, Python, Perl, Shell scripting, Infrastructure.

Experience in Monitoring Alerting, and Job Scheduling Systems

Being comfortable with frequent, incremental code testing and deployment

Strong grasp of automation / DevOps tools - Ansible, Jenkins, SVN, Bitbucket

Tools Involved -

ETL tools: Hadoop Stack

Job Scheduling tools: Autosys

BI tools: Tableau ; Tableau dashboard building connecting Hadoop-Hive Tables is equally preferred