Big Data Engineer

Phoenix, AZ
BE/ B.Tech
7 Years
Big Data
  • Very strong server-side Java experience, especially in an open source, data-intensive, distributed environments.
  • Strong previous professional experience building Distributed Solutions dealing with high volumes of data.
  • Hands on experience on HDFS, Hive, Pig, Sqoop and NOSQL.
  • Experience/ knowledge working with batch processing/ real-time systems using various open source technologies like Solr, Storm, Kafka, etc.
  • Experience in Apache Spark Batch and/or Spark Streaming (at least 6 months)
  • Good understanding of algorithms, data structure, performance optimization techniques and exposure to complete SDLC and PDLC
  • Well aware of architectural concepts (Multi-tenancy, SOA, SCA etc.) and NFR’s (performance, scalability, monitoring etc.)
  • Implementing various solutions arising out of large data processing (GB’s/ PB’s) over various NoSQL, Hadoop and MPP based products—both on-premise and in the cloud
  • Actively participating in various architecture and design calls with Big Data customers
  • Developing Hive scripts and being involved in writing MapReduce jobs
  • Implementing complex projects dealing with considerable data size (GB/PB) and with high complexity
  • Leveraging your experience with Hadoop and software engineering to help our customers drive value from their data
  • Working with Sr. Architects and providing implementation details to the Offshore team
  • Conducting sessions/ writing whitepapers/ Case Studies pertaining to Big Data
  • Being responsible for timely and quality deliveries
  • Fulfilling organizational responsibilities – sharing knowledge and experience with other passionate Impetus professionals, conducting various technical development sessions and training on new technologies
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