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Data Engineer - H1B/GC/USC

Job Id : 11556

Jobtitle : Data Engineer - H1B/GC/USC

Location : Wilmington, VA

Company Name : E-Solution INC

Industry : Information Technology

Salary : $87,300 - $122,117  YEAR

Job type : Fulltime

Posted on: 2020-02-13

Required Skills : AWS, Docker, Kubernetes, Python

Benefits : No benefits are available

Job Description :

  • Experience with object-oriented/object function scripting languages: Strong Python Programming Background  
  • Experience with big data tools: Apache Spark, Spark-Streaming, etc.
  • Experience AWS Devops with Kubernetes and Conternization, Docker
  • Experience with AWS Services like EMR, S3, Lambda, SNS, SQS, Snowflake
  • Experience with data pipeline and workflow management tools: NiFi
  • Experience with AWS cloud services: S3, EC2, EMR, RDS, Redshift  


  • Create and maintain optimal data pipeline architecture,
  • Assemble large, complex data sets that meet functional / non-functional business requirements.
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
  • Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
  • Work with data and analytics experts to strive for greater functionality in our data systems

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