AWS Data Engineer with Spark/Scala Background - Newark, United States - PamTen

    PamTen
    PamTen Newark, United States

    2 weeks ago

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    Contract
    Description
    Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience
  • Experience implementing, supporting data lakes, data warehouses and data applications on AWS for large enterprises
  • Solid experience of AWS services such as CloudFormation, S3, Athena , Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
  • Solid experience implementing solutions on AWS based data lakes.
  • Experience in AWS data lake/data warehouse/business analytics
  • Experience in system analysis, design, development, and implementation of data ingestion pipeline in AWS
  • Knowledge of ETL/ELT
  • End-to-end data solutions (ingest, storage, integration, processing, access) on AWS
  • Architect and implement CI/CD strategy for EDP
  • Implement high velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred)
  • Migrate data from traditional relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift
  • Migrate data from APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift
  • Implement POCs on any new technology or tools to be implemented on EDP and onboard for real use-case
  • AWS Solutions Architect or AWS Developer Certification preferred
    • Requirements :
  • 5+ years of experience as Data engineer
  • Experience developing business applications using SQL databases.
  • Experience working Cloud (AWS preferred)
  • Should have good experience with AWS Services – S3, Athena, Glue, Lambda, Step Functions, SQS, Redshift.
  • 3+ Years of experience with Spark / Scala.
    • ​
    Responsibilities:
  • Designing, building and maintaining efficient, reusable, and reliable architecture and code.
  • Build reliable and robust Data ingestion pipelines (within AWS, onprem to AWS ,etc)
  • Ensure the best possible performance and quality of high scale data engineering project
  • Participate in the architecture and system design discussions
  • Independently perform hands on development and unit testing of the applications;
  • Collaborate with the development team and build individual components into complex enterprise web systems;
  • Work in a team environment with product, production operation, QE/QA and cross functional teams to deliver a project throughout the whole software development cycle;
  • Responsible to identify and resolve any performance issues
  • Keep up to date with new technology development and implementation
  • Participate in code review to make sure standards and best practices are met