AWS Data Engineer

Job Title: AWS Data Engineer Location: Remote Job Type: Contract Job Description: We are looking for an experienced AWS Data Engineer with strong hands-on expertise in AWS Glue, Amazon Redshift, S3, Python, PySpark, and SQL to design, develop, and maintain scalable cloud data pipelines and enterprise data warehouse solutions.

Responsibilities

Design, develop, and maintain scalable ETL/ELT data pipelines using AWS Glue, Python, PySpark, and SQL. Develop AWS Glue Jobs, Crawlers, Workflows, and Data Catalog solutions for automated data ingestion, transformation, and processing. Build and optimize data pipelines to ingest structured and semi-structured data from multiple sources into Amazon S3 and Amazon Redshift. Design and develop Amazon Redshift data warehouse solutions, including tables, views, stored procedures, and analytical data models. Develop complex SQL queries for data transformation, validation, reconciliation, and analytical reporting. Optimize Redshift performance using appropriate distribution styles, sort keys, table design, workload optimization, and query tuning techniques. Implement incremental and full-load ETL strategies, including data validation, error handling, reconciliation, and restartable processing. Integrate AWS Glue, S3, Redshift, Athena, and other AWS services to build scalable cloud data platforms. Develop PySpark-based transformations for large-volume datasets and optimize Spark jobs for performance and reliability. Implement data quality checks to ensure data completeness, accuracy, consistency, and integrity across source and target systems. Work with AWS Glue Data Catalog and crawlers to manage metadata and support schema discovery for enterprise datasets. Monitor and troubleshoot production data pipelines, Glue jobs, and Redshift workloads to ensure high availability and reliability. Support migration of legacy ETL and data warehouse workloads to AWS cloud-native platforms. Implement security and access controls using AWS IAM roles, policies, and encryption mechanisms. Collaborate with Data Architects, BI Developers, Business Analysts, and other engineering teams to translate business requirements into scalable data solutions. Participate in CI/CD and infrastructure automation using tools such as Git, GitHub Actions, Jenkins, Terraform, or CloudFormation. Required Skills 5+ years of experience in Data Engineering Strong hands-on experience with AWS Glue Strong experience with Amazon Redshift Proficiency in Python and PySpark Advanced SQL skills Experience with Amazon S3 Experience with AWS Glue Data Catalog and Crawlers Experience with AWS Athena Strong understanding of ETL/ELT concepts and data warehousing Experience with dimensional modeling, fact/dimension tables, and data marts Experience with performance tuning and troubleshooting of large-scale data pipelines Preferred Skills Experience with Databricks / Apache Spark Experience with AWS EMR Experience with Apache Airflow Experience with Snowflake Experience with Terraform Experience with Power BI or Tableau Experience with cloud migration and legacy ETL modernization Experience working with healthcare, finance, telecom, or other enterprise data environments