job description

• 3.5 - 5.5 years of good hands-on exposure with Big Data technologies Py Spark (Data frame and Spark SQL), Hadoop, and Hive 
• Good hands-on experience of python and Bash Scripts 
• Good understanding of SQL and data warehouse concepts 
• Strong analytical, problem-solving, data analysis and research skills 
• Demonstrable ability to think outside of the box and not be dependent on readily available tools 
• Excellent communication, presentation and interpersonal skills are a must 

Good to have: 

• Hands-on experience with using Cloud Platform provided Big Data technologies (i.e. IAM, Glue, EMR, RedShift, S3, Kinesis) 
• Orchestration with Airflow and Any job scheduler experience 
• Experience in migrating workload from on-premises to cloud and cloud to cloud migrations 

Roles & Responsibilities

• Develop efficient ETL pipelines as per business requirements, following the development standards and best practices. 
• Perform integration testing of different created pipeline in AWS env. 
• Provide estimates for development, testing & deployments on different env. 
• Participate in code peer reviews to ensure our applications comply with best practices. 
• Create cost effective AWS pipeline with required AWS services i.e S3, IAM, Glue, EMR, Redshift etc.