Job Description :

Job Title: Big Data Consultant (PySpark or Spark-Scala)

Location:Dallas

Type:Permanent

Experience:4-7 years (relevant)

Notice: Immediate

Job Description:
 

Must Have: Spark, Spark Core, PySpark, Python, Scala, HDFS, Hadoop, Kafka, Data Ingestion, Data Quality

Education: Minimum Bachelor’s degree in Computer Science, Engineering, Business Information Systems, or related field. Masters in Computing related to scalable and distributed computing is a major plus


 Key Responsibilities:

  • Develop Big Data applications using PySpark or Scala-Spark on Hadoop, Hive and/or Kafka, HBase, MongoDB
  • Build Feature Engineering, Scoring / Machine Learning models
  • Deployment on Cloud platforms 

Experience & Skillset: MUST-HAVE

  • Total IT / development experience of 7+ years
  • Experience in PySpark or Spark-Scala developing Big Data applications on Hadoop, Hive and/or Kafka, HBase, MongoDB
  • Technical Design and Onsite-Offshore coordination
  • Deep knowledge of Spark libraries on Python or Scala to develop and debug complex data engineering challenges
  • Experience in developing sustainable data driven solutions with current new generation data technologies to drive our business and technology strategies
  • Exposure in deploying on Cloud platforms
  • At least 3 years of development experience on designing and developing Data Pipelines for Data Ingestion or Transformation using PySpark or Spark-Scala
  •  At least 4 years of development experience in the following Big Data frameworks: File Format (Parquet, AVRO, ORC), Resource Management, Distributed Processing and RDBMS
  • At least 4 years of developing applications in Agile with Monitoring, Build Tools, Version Control, Shell Scripting, Unit Test, TDD, CI/CD, Change Management to support DevOps
  • Prior experience on ETL or SQL or other Data technologies 

GOOD-TO-HAVE

  •  Banking domain knowledge
  • Hands-on experience in SAS toolset / statistical modelling migrating to Machine Learning models
  • Digital Marketing Machine Learning models and use cases
  • ETL / Data Warehousing and Data Modelling experience prior to Big Data experience
  • Deep knowledge on AWS stack for big data and machine learning
             

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