Job Description

We are looking for a AWS Data Engineer who will be able to design and build solutions for one of our Fortune 500 Client programs, which aims towards building a Enterprise Data Lake on AWS Cloud platform and build Data pipelines by developing several AWS Data Integration, Engineering & Analytics resources.

Key Responsibilities

  • Perform technical assessment across Glue ETL and Lambda functions
  • Build the Python programs across the Glue ETL and Lambda functions
  • Build PySpark based data pipeline resources on AWS EMR Clusters & Glue ETL requiring in-depth knowledge on majority of Hadoop and NoSQL databases as well
  • Optimize performance of Spark applications in Hadoop using configurations around Spark Context, Spark-SQL, Data Frame, and Pair RDD’s
  • Create documentation for user adoption, deployments, runbook, and support client users forenablement or for any issues encountered.
  • Ability to monitor, troubleshoot and debug failures using AWS CloudWatch and Grafana
  • Perform code reviews with the team and enable them to develop code for complex scenarios
  • Liaise with all SDLC support teams to ensure seamless deployment to controlled environments and thus ensuring application robustness

    • Qualifications:

  • Bachelor’s Degree or equivalent in computer science or related and minimum 7+ years of experience
  • Certified on one of – Solution Architect OR Data Analytics Specialty by AWS
  • 2+ years of hands-on experience on AWS S3, Glue ETL & Catalog, EMR, Lamba Functions,Athena & Kafka
  • Require 2+ years of hand-on experience on PySpark programming
  • Experience in writing complex SQL queries
  • Preferred expertise on MongoDB, Oracle & Hadoop (Hive, Hdfs, Yarn)
  • Require Technical Coordination skills to drive requirements and technical design with multipleteams
  • Financial services and Healthcare industry experience preferred
  • Requires aptitude to help build skillset within organization

    • Location: Pune / Hyderabad (Even for Chicago / New York)

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