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
Responsibilities:
- 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
Required education
Bachelor's Degree
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 Azure
- Experience in DataBricks / Azure HDInsight / Azure Data Factory, Synapse, SQL Server DB
- Exposure to streaming solutions and message brokers like Kafka technologies
- Experience Unix / Linux Commands and basic work experience in Shell Scripting
Preferred technical and professional experience
- Certification in Azure and Data Bricks or Cloudera Spark Certified developers
