Description

You will design and implement large-scale data solutions covering ingestion, curation, quality, visualization, and distribution.

Responsibilities

• Build and manage data pipelines using Informatica and Snaplogic.
• Write structured, testable PySpark code to implement machine learning use cases in production.
• Develop UNIX shell scripts to automate ETL loading and extraction processes.
• Manage and query data within Google BigQuery and AWS Redshift repositories.
• Create test plans, test cases, and scripts to perform data validation.

Required Skills

• 5+ years of experience in data engineering.
• Proficiency with Informatica and Snaplogic.
• Experience with Tableau and MicroStrategy for data visualization.
• Hands-on experience with Google BigQuery and AWS Redshift.
• Strong PySpark skills for production-grade machine learning implementations.
• Ability to write and automate UNIX shell scripts.
• Experience designing ETL processes and data ingestion workflows.
• Background in data testing and validation methodologies.
• Any Graduate degree.

Key Skills

Education

Any Graduate