Big Data Engineer – Consultant

  • Full-time

Company Description

We are a top-tier global consulting company. Join us and help transform leading organizations and communities around the world.  The sheer scale of our capabilities and client engagements and the way we
collaborate, operate and deliver value, provides an unparalleled opportunity to grow and advance.  Make delivering innovative work part of your extraordinary career.

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.


We offer a very generous benefits & perks package for our employees and their families.

Job Description

he Big Data Engineer Consultant empowers clients to turn information into action by gathering, analyzing and modeling client data which enables smarter decision making.  You will use a broad set of analytical tools and techniques to develop quantitative and qualitative business insights.  You will work with partners to integrate systems and data quickly and effectively, solving technical challenges and working in different business environments. You will architect, design and implement Hadoop and NoSQL-based full scale solutions that includes data acquisition, storage, transformation, security, data management, and data analysis

Do you have a pulse on new technologies and a desire to change the way business gets done?  Do you want to implement emerging solutions for some of the most successful companies around?  If yes, this opportunity is for you.

Qualifications

Must-haves:


  • At l least 2 years of  experience building and deploying Java applications on Linux/Unix in a production environment
  • At least 1 year of experience designing and building  large scale data loading, manipulation, processing, analysis, blending, and exploration solutions using Hadoop/NoSQL technologies , such as HDFS, Hive, Sqoop, Flume, Spark, Kafka, HBase, Cassandra, MongoDB, etc
  • At least 1 year of experience with one or more of the following technologies: MapReduce Java, Spark, Pig, Hadoop Streaming, HiveQL, Perl/Python/PHP  for data analysis of  production Hadoop/NoSQL applications
  • A solid understanding of infrastructure planning, scaling, design, and operational considerations that are unique to Hadoop, NoSQL and other emerging data technologies
  • Bachelor’s Degree  in Computer Science or a related discipline
  • Ability to travel to clients’ sites Monday – Thursday/ Friday

Pluses:


  • Experience designing and implementing relational data models working with RDBMS
  • Experience working with traditional ETL tools
  • Experience developing REST web services
  • Designing and building  statistical analysis models, machine learning models, other analytical modeling, using such technologies as: R, MLib, Mahout, Spark, GraphX
  • Experience implementing large scale cloud data solutions using AWS data services e.g. EMR, Redshift
  • Experience designing and implementing  production data solutions using emerging technologies such as Hadoop Ecosystem, NoSQL, In-Memory Data Technologies, Data Munging Technologies.
  • Designing and building different data access patterns from Hadoop/NoSQL data stores
  • Managing and Modeling data using Hadoop and NoSQL data stores
  • Experience with data munging / data wrangling tools and technologies

Additional Information

  • Applicants must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization
  • Candidates can live anywhere in the United States, as long as they are within a drivable distance from a major airport
  • Candidates must be ready to travel to clients’ sites Monday – Thursday/ Friday