Data Engineer-Data Platforms-AWS

Introduction

A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology

Your Role And Responsibilities

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform

• Experienced in building data pipelines to Ingest, process, and transform data from files, streams and databases. Process the data with Spark, Python, PySpark, Scala, and Hive, Hbase or other NoSQL databases on Cloud Data Platforms (AWS) or HDFS
• Experienced in develop efficient software code for multiple use cases leveraging Spark Framework / using Python or Scala and Big Data technologies for various use cases built on the platform
• Experience in developing streaming pipelines
• Experience to work with Hadoop / AWS eco system components to implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Total 5 - 7+ years of experience in Data Management (DW, DL, Data Platform, Lakehouse) and Data Engineering skills
• Minimum 4+ years of experience in Big Data technologies with extensive data engineering experience in Spark / Python or Scala.
• Minimum 3 years of experience on Cloud Data Platforms on AWS; Exposure to streaming solutions and message brokers like Kafka technologies.
• Experience in AWS EMR / AWS Glue / DataBricks, AWS RedShift, DynamoDB
• Good to excellent SQL skills
  
  

Preferred Technical And Professional Experience

• Certification in AWS and Data Bricks or Cloudera Spark Certified developers
• AWS S3, Redshift, and EMR for data storage and distributed processing.
• AWS Lambda, AWS Step Functions, and AWS Glue to build serverless, event-driven data workflows and orchestrate ETL processes