AWS Data Engineer

Job Description – Data Engineer

We are looking for an experienced Data Engineer with strong expertise in Python, PySpark, SQL, and AWS Cloud . The candidate will be responsible for building scalable data pipelines, developing ETL workflows, and working with AWS data engineering services.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL workflows .
• Develop data processing solutions using Python and PySpark .
• Write complex and optimized SQL queries for data extraction, transformation, and analysis.
• Build and manage ETL pipelines using AWS Glue .
• Work with AWS Glue Data Catalog for metadata and data discovery.
• Use Amazon S3 for scalable and secure data storage.
• Develop serverless data-processing solutions using AWS Lambda .
• Implement event-driven workflows using Amazon EventBridge .
• Orchestrate data pipelines and workflows using AWS Step Functions .
• Use Amazon Athena for querying and analyzing data stored in Amazon S3.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Collaborate with data analysts, data scientists, and other engineering teams to deliver data solutions.

Required Skills

• Strong hands-on experience with Python
• Strong experience with PySpark
• Advanced SQL
• Hands-on experience with AWS Cloud
• Amazon S3
• AWS Glue – ETL & Data Catalog
• AWS Lambda
• Amazon EventBridge
• AWS Step Functions
• Amazon Athena
• Good understanding of ETL/ELT concepts, data pipelines, and data processing
• Strong problem-solving and analytical skills

Preferred

• Experience with AWS-based data engineering architectures
• Knowledge of data warehousing and data lake concepts
• Experience with performance optimization and production data pipelines