Job Description :

Job Title: AWS Services / AWS Data pipeline

Location: Plano TX

Duration: 1 year

Job Description:

  • 8+ years of experience in large data processing platform, ETL/ELT pipelines, and data techs for ingesting, processing and analytics using Bigdata technology.
  • 2+ years of strong technical Experience with AWS cloud services such as S3, IAM, EC2, EMR, RDS, Redshift, SNS, Cloudwatch, Glue, DMS, SCT, Lambda.
  • Build and configure a virtual data center in AWS to support Enterprise Data Warehouse hosting including Virtual Private Cloud (VPC), Public and Private Subnets, Security Groups, Route Tables and Elastic Load Balancer.
  • Experience with AWS Cloud Platforms, managing cloud components, including cluster management, Kubernetes, or other containerized services, storage, and workspace management.
  • Experience design and building scalable Data Warehousing/Data Lake Solution and Business Intelligence
  • 5+ years of experience (Sr-level) Strong Programming experience with object-oriented/object function scripting languages: Python, Spark, Scala, Shell Scripting
  • Knowledge of business intelligence and data warehousing design principles and industry best practices
  • Experience in DevOps engineering for CI\CD: with Jenkins, GitHub, Docker, and Kubernetes.
  • 2+ Years of experience with relational SQL, Snowflake and NoSQL databases, including Postgres and Cassandra.
  • 2+ years of experience in Attunity, Kafka, AMQ or similar streaming tools.
  • Experience on data migration from on prem to cloud.
  • Knowledge of load balancing, security controls and distributed processing capabilities.
  • Ability to troubleshooting issues as and when arisen.
  • Technical/functional support for pipeline related activities.
  • POD Cross functional expert and work with stakeholders including the Executive, Product, Data / Solution Architect and Design teams to assist with data-related technical issues and support validating data infrastructure needs.
  • Involved in supporting data modelling activities as part of building the data warehouse.
  • Deep understanding of relational database design concepts and SQL programming

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