Infrastructure Engineer Consultant Hadoop

Job Title: Infrastructure Engineer Consultant Hadoop

Job Purpose:

• This position is responsible for collaborating with Solutions Engineering, Infrastructure Operations, and Infrastructure Service Management teams
• in the design and build of infrastructure solutions/blueprints for the area of responsibility.
• Participating in the design and build of repeatable patterns (build-kits) to improve deployment for non-prod and prod environments.
• Transitioning knowledge to Infrastructure Operations.

Required Job Qualifications:

• Bachelor's Degree and: 5 years in Information Technology or relevant experience or;
• Technical Certification and/or College Courses and: 7-year Information Technology experience or;
• 9 years: Information Technology experience.
• Have hands-on experience in working with Hadoop distribution platforms like Hortonworks, Cloudera, and others.
• Candidate should be ready for Hadoop on-call support if and when needed.
• Expert in implementing and troubleshooting Hive, Pig, Storm, Kafka, Nifi, Elastic Search, Solr, HBase applications.
• Working knowledge of Ruby or Python and known DevOps tools like Git and GitHub.
• Experience in a scripting language to automate Infrastructure deployment tasks.
• Ability to simplify & standardize complex concepts/processes.
• Understanding of business priorities (e.g., vision), trends (e.g., industry knowledge) and markets (e.g., existing/planned).
• Oral & written communications.
• Ability to prioritize and make trade-off decisions.
• Drive cross-functional execution.
• Adaptability and ability to introduce/manage change.
• Teamwork and collaboration.
• Organized and detail oriented.

Preferred Job Qualifications:

• Experience in Hadoop Application Infrastructure Engineering and Development Methodology background.
• Experience with Ambari, Hortonworks, and HDInsight.
• Experience with Cloudera Technology (Azure/AWS).
• Experience with Streaming Technology (e.g. Kafka).
• Experience with Kerberos, TLS encryption, SAML, LDAP.
• Knowledge in the Cloud (Azure/AWS) big data solutions using EMR, HDInsight, Kinesis, Azure, Event Hubs, etc.