Data Engineer - AWS

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Requirements:

• 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
• Hands-on experience in designing and building data pipelines.
• Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, and Amazon Redshift.
• Strong experience with Databricks, Pyspark for data processing and analytics.
• Solid understanding of data modeling, database design principles, and SQL and Spark SQL.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
• Strong problem-solving skills and attention to detail.

Responsibilities:

• Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, and Amazon Redshift.
• Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.
• Build and maintain orchestration workflows using Apache Airflow for automating data pipeline execution, scheduling, and monitoring.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.
• Optimize data pipelines for performance, reliability, and cost-effectiveness utilizing AWS best practices.