Description

You will build and maintain ETL data pipelines using AWS services. You write, optimize, and maintain SQL queries for data transformation. You develop Python and PySpark scripts for data processing and automation. You support data ingestion, transformation, and validation from structured and semi-structured sources. You participate in data quality checks, monitoring, and basic troubleshooting. You collaborate with senior engineers and stakeholders to understand data requirements. You follow coding standards, security policies, and data governance guidelines. You document data pipelines, workflows, and technical designs.

Responsibilities

• Develop and maintain ETL pipelines using AWS Glue, S3, Redshift, and Lambda
• Write and optimize SQL queries for data transformation and analysis
• Develop Python and PySpark scripts for data processing and automation
• Support data ingestion, transformation, and validation from multiple sources
• Perform data quality checks, monitoring, and basic troubleshooting

Required Skills

• Bachelor’s degree in Computer Science, IT, Engineering, or related field
• 0–3 years of experience in data engineering or cloud-based projects
• Working knowledge of AWS data services (S3, AWS Glue, Redshift, Lambda)
• Strong proficiency in SQL
• Basic to intermediate proficiency in Python
• Understanding of ETL concepts, data warehousing, and relational databases
• Familiarity with cloud computing fundamentals and distributed systems
• Experience with Git or version control systems

Key Skills

Education

Bachelor's degree