Data Engineer-Data Platforms-Azure

Introduction

In this role, youll 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 Azure 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 and Hive, Hbase or other NoSQL databases on Azure Cloud Data Platform 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 / Azure 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
  
  

• Total 5-8 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 Azure;
• Experience in Data Bricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB
• Good to excellent SQL skills
  
  

• Certification in Azure and Data Bricks or Cloudera Spark Certified developers
• Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB
• Knowledge or experience of Snowflake will be an added advantage