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