AWS Data Engineer

You will focus on backend development using the AWS Data Integration and Storage tech stack to build and automate data pipelines.

Responsibilities

• Design and implement scalable ETL processes and data pipelines using AWS Glue, AWS Lambda, and Apache Spark.
• Transition existing AWS data pipelines and procedures developed for the Department of Health and Human Services.
• Develop and maintain data models, schemas, and transformation logic for data warehousing and analytics.
• Implement data ingestion from various sources into Amazon S3, Amazon Redshift, or Amazon DynamoDB.
• Optimize pipelines for performance and cost-efficiency while monitoring for bottlenecks and consistency issues.
• Collaborate with Data Engineers, Analysts, and Report Developers to automate recurring data requests and troubleshoot issues.

Required Skills

• 5+ years of professional experience as a Data Engineer with a focus on AWS services.
• Expertise in AWS Glue, AWS Lambda, and AWS Spark.
• Hands-on experience with AWS Data Migration Services, AWS RDS, Amazon S3, Amazon Redshift, and Amazon DynamoDB.
• Strong proficiency in SQL, Microsoft SQL Server, and MySQL.
• Experience with Microsoft SQL Server Integration Services (SSIS).
• Proficiency in programming languages such as Python, Scala, or Java for data processing.
• Deep understanding of data modeling, data warehousing, and data integration concepts.
• Ability to follow standard practices for migrating changes to test and production environments.
• Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.