Sr. Big Data Consultant - San Francisco - Bay Area

Description

Are you a Big Data specialist? Do you have Data Warehousing and/or Hadoop experience? Do you like to solve the most complex and high scale (billion + records) data challenges in the world today? Do you want to have an impact in the development and use of new data analytics technologies? Would you like a career that gives you opportunities to help customers and partners use cloud computing web services to do big new things faster, at lower cost? Do you like to gain the deepest customer and partner insights using Cloud computing technologies?

At AWS, we're hiring highly technical cloud computing architects to collaborate with our customers and partners on key engagements. Our consultants will develop and deliver proof-of-concept projects, technical workshops, and support implementation projects. These professional services engagements will focus on customer solutions such as HPC, batch data processing, Big Data and Business intelligence. This role will specifically focus on Data processing capabilities and helping our customers and partners to remove the constraints that prevent our customers from leveraging their data to develop business insights.

Basic Qualifications

  • Customer facing skills to represent AWS well within the customer's environment and drive discussions with senior personnel regarding trade-offs, best practices, project management and risk mitigation
  • Write and produce technical documentation, knowledgebase articles
  • Work closely with AWS EMR teams at all levels to help ensure the success of project consulting engagements with customer
  • Work directly with customers' technical resources to devise and recommend solutions based on the understood requirements
  • Help design and implement Hadoop architectures and configurations for customer
  • Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment.
  • Analyze complex distributed production deployments, and make recommendations to optimize performance
  • Highly technical and analytical, possessing 5 or more years of IT platform implementation experience.
  • Keep current with the Hadoop Big Data ecosystem technologies
  • Travel is up to 50% regionally. (Customers within Southern California or West coast).

Preferred Qualifications

  • Bachelor's degree in Computer science or equivalent experience
  • Hands on experience leading large-scale global data warehousing and analytics projects
  • 2+ years designing and deploying 3 tier architectures or large-scale Hadoop solutions
  • Demonstrated industry leadership in the fields of database, data warehousing or data sciences.
  • Strong experience implementing software and/or solutions in AWS environment
  • Strong understanding with various enterprise security solutions such as LDAP and/or Kerberos
  • Familiarity with scripting tools such as bash shell scripts, Python and/or Perl
  • Implementation and tuning experience specifically using Amazon Elastic Map Reduce
  • Experience implementing data transformation and processing solutions using Apache PIG
  • Experience designing data queries against data in the HDFS environment using tools such as Apache Hive/Impala/Shark
  • Track record of implementing AWS services in a variety of distributed computing, enterprise environments.
  • Significant previous work writing to network-based APIs, preferably REST
  • Ability to understand big data use-cases, and recommend standard design patterns commonly used in Hadoop-based deployments.
  • Strong understanding of the Java ecosystem and enterprise offerings, including debugging and profiling tools, logging and monitoring tools (log4j, JMX), and security offerings (Kerberos/SPNEGO).
  • Demonstrable experience using R and the algorithms provided by Mahout
  • Experience with Storm, Kafka, Flume, HCatalog
  • Knowledge of the data management eco-system including: Concepts of data warehousing, ETL, data integration, etc.

    For more information on Amazon Web Services, please visit http://aws.amazon.com


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