Role: Sr. AWS Data Engineer Location: Remote Type of position: Contract Job description: Responsibilities: • Collaborate with cross-functional teams including Data Scientists, Analysts, and Engineers to gather data requirements and build scalable data solutions. • Design, develop, and maintain complex ETL pipelines using AWS Glue and PySpark, ensuring efficient data processing across batch and streaming workloads. • Integrate and manage data storage and retrieval using AWS DynamoDB and Snowflake, optimizing for performance and scalability. • Ensure data integrity, quality, and security across data pipelines, applying best practices for encryption, IAM, and compliance. • Monitor and troubleshoot pipeline issues, continuously optimizing for cost and performance across AWS services. • Stay current with advancements in AWS Glue, PySpark, and data infrastructure tools, and recommend improvements where applicable. Experience / Minimum Requirements: • 8+ years of experience as a Data Engineer, with strong hands-on expertise in AWS Glue, PySpark, AWS DynamoDB, and Snowflake. • Deep understanding of Spark architecture, distributed processing, and performance tuning techniques. • Strong grasp of data modeling, schema design, and data warehouse concepts. • Experience with AWS data ecosystem including S3, Lambda and Glue Catalog. • Proficiency in Python (PySpark) for data transformation and automation tasks. • Familiarity with CI/CD practices and infrastructure-as-code tools such as Terraform is a plus. • Excellent communication and problem-solving skills, with the ability to work independently and in a team environment.