Big Data Engineer - Manager
Washington , District of Columbia
September 23, 2017


  • Bachelor's degree in Computer Science, Engineering, Technical Science or 5 years of IT/Programming experience
  • Minimum 2+ years of designing, building and operationalizing large scale applications using Hadoop and NoSQL components -  HDFS, HBase, Hive, Sqoop, Flume, Spark, MapReduce, Kafka, Cassandra, MongoDB etc. in production
  • Minimum 2+ years of organizing and architecting data at scale for Hadoop/NoSQL data stores
  • Minimum 1+ year of MapReduce coding, including Java, Python, Pig programming, Hadoop Streaming, HiveQL for data analysis of  production applications
  • Minimum 2+ years of administering and managing large production Hadoop/NoSQL clusters
  • 2+ years of hands-on experience designing and implementing data applications in production using emerging data technologies such as Hadoop Ecosystem (MapReduce, Hive, HBase, Spark, Sqoop, Flume, Pig, Kafka etc.), NoSQL (e.g. Cassandra, MongoDB), In-Memory Data Technologies, Data Munging Technologies,
  • Minimum 2+ year of experience implementing large scale cloud data solutions using AWS data services e.g. EMR, Redshift
  • Minimum 2+ years working with traditional as well as Big Data ETL tools
  • Minimum 2+ years designing and implementing relational data models working with RDBMS
  • Minimum 2+ years of experience designing and building REST web services
  • Minimum 2+ years of building and deploying Java apps to production
  • Minimum 1+ years of administering and managing large production Hadoop/NoSQL clusters
  • Responsibilities include the following:
    • Architect modern data solutions in a hybrid environment of traditional and modern data technologies such as Hadoop, NoSQL
    • Create technical and operational architectures for these solutions incorporating Hadoop, NoSQL and other modern data technologies
    • Implement and deploy custom solutions/applications using Hadoop/NoSQL
    • Lead and guide implementation teams and provide technical subject matter expertise in support of the following:
      • Designing, implementing and deploying ETL to load data into Hadoop/NoSQL
      • Security implementation of a Hadoop/NoSQL solutions
      • Managing data in Hadoop/NoSQL co-existing with traditional data technologies in a hybrid environment
      • Troubleshooting production issues with Hadoop/NoSQL
      • Performance tuning of a Hadoop/NoSQL environment
  • Modeling data for Hadoop/NoSQL data stores and building applications around them
  • Architecting and implementing metadata management solutions around Hadoop and NoSQL in a hybrid environment
  • Architecting and implementing large scale Hadoop or NoSQL operations in a production environment
  • Re-architecting and rationalizing traditional data environments with Hadoop or NoSQL technologies
  • Experience implementing data wrangling and data blending solutions for enabling self-service solutions
  • Experience with identifying, designing and implementing functional solutions for big data use cases in different industries
  • 3 years industry systems development and implementation experience OR Minimum of 2 years of data loading, acquisition, storage, transformation, and analysis
  • Experience with the following task using above mentioned emerging technologies :
    • Specifying technical architecture of a Hadoop / NoSQL / Spark solutions
    • Architecting infrastructure for large scale Hadoop/NoSQL/in memory applications (put in production)
    • Design and Implementation of custom applications using emerging data technologies
    • Design and Implementation of  large scale data loading, manipulation, processing, analysis and exploration using Hadoop/NoSQL technologies
    • Designing and building statistical analysis models, machine learning models, other analytical modeling using these technologies on large data sets (e.g. MLib, Mahout, Spark, R)
    • Administration of large production cluster Hadoop/NoSQL
    • Performance tuning large Hadoop/NoSQL/In-Memory clusters
    • Data migration from existing system into Hadoop/NoSQL
    • Modernizing traditional data warehousing solutions incorporating Hadoop/NoSQL in the mix
    • Prior experience with large scale data manipulation, management and analysis  with large data sets on platforms such as Pivotal, Aster, Vertica
    • Additional Hands-on experience with related/complementary open source software platforms and languages such as Java, Linux, Apache, Perl/Python/PHP, Scala)
    • Hands-on experience building visual analytics applications around data from a distributed hybrid data platform
    • Designing and implementing large scale data solutions using AWS big data and analytics services e.g. EMR, RedShift
  • Client facing skills: ability to build trusted relationships with client stakeholders and act as a trusted adviser
It is our intention for our people to work where they live. However, in the context of our profession and serving our clients there may be times when you will need to travel.
All of our consulting professionals receive comprehensive training covering business acumen, technical and professional skills development. You'll also have opportunities to hone your functional skills and expertise in an area of specialization. We offer a variety of formal and informal training programs at every level to help you acquire and build specialized skills faster. Learning takes place both on the job and through formal training conducted online, in the classroom, or in collaboration with teammates. The sheer variety of work we do, and the experience it offers, provide an unbeatable platform from which to build a career.
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with Accenture (i.e., H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant status).

Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.

Accenture is an EEO and Affirmative Action Employer of Females/Minorities/Veterans/Individuals with Disabilities.


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