AWS Data Engineer

Resource 1 is in need of a Data Engineer for a remote contract position with our client in Chicago, Illinois. The selected individual will join a team responsible for the migration of a data warehouse from Microsoft Azure to AWS. This position requires deep expertise in AWS technologies such as Redshift, EC2, and Glue. Will play a pivotal part in migrating, optimizing, and managing data infrastructure on AWS. Individual will collaborate with cross-functional teams to ensure a seamless transition and optimize the performance of the data warehouse on AWS.

Key Responsibilities:

Migration of data warehouse from Azure to AWS

Design, configure, and optimize Amazon Redshift clusters to store and process large datasets. Work on the performance tuning of Redshift queries and ensure high availability and scalability.

Develop ETL pipelines using AWS Glue to facilitate data integration between sources and Redshift.

Implement monitoring tools and strategies for performance optimization of AWS resources (Redshift, Glue, EC2) and ensure smooth data flow across the infrastructure.

Work closely with Data Analysts, Data Scientists, and other stakeholders to design data models, build pipelines, and ensure the availability of clean, accurate, and reliable data.

Use Redshift ML to build and deploy machine learning models within the Redshift environment.

Advocate for cloud architecture best practices, data security, and cost-efficient strategies.

Required Qualifications:

• 5+ years of experience as a Data Engineer, with a strong focus on AWS technologies.
• Experience migrating data warehouse from Azure to AWS.
• Experience working with AWS Redshift, AWS Glue, and AWS EC2.Expertise in designing/ building scalable ETL pipelines and data architectures on AWS.
• Expertise in Redshift (clustering, querying, schema design, performance tuning).Strong knowledge of AWS Glue for ETL workflows and data integration. Proficient in AWS EC2 for cloud compute management. Familiarity with Redshift ML (optional, but a plus).Experience with AWS services such as S3, IAM, Lambda, and CloudWatch is beneficial.
• Familiarity with cloud cost optimization strategies.
• Proficiency in SQL and Python for data processing and automation.

Preferred Qualifications:

Redshift ML and integrating machine learning models within the Redshift ecosystem.

AWS CloudFormation or Terraform for infrastructure automation.

DevOps practices and CI/CD pipelines in context of data engineering.