Description

You will build and deploy data pipelines and serverless ETL solutions within an AWS cloud environment.

Responsibilities

• Develop data pipelines using AWS Glue, Apache Spark, and Step Functions.
• Build, prototype, and deploy ETL jobs using Python, Lambda, and PySpark.
• Assemble complex datasets using serverless services, SQS, and Athena.
• Integrate custom software solutions with automated deployment technologies and AWS CloudFormation.
• Collaborate with architecture and data center teams to analyze infrastructure needs through proof of concept and testing.

Required Skills

• 8-12 years of experience with a Bachelor's degree, or 6-10 years with a Master's degree.
• Extensive experience with AWS big data technologies and cloud-native ETL tools.
• Proficiency in Python and PySpark.
• Experience with DynamoDB and SQL querying.
• Hands-on experience with Kubernetes and containerization.
• Working knowledge of Delta Lake.
• Experience with data catalog tools including AWS Glue Catalog and DataHub.
• Proficiency with version control systems, specifically CodeCommit.
• Experience using Jira for issue and problem tracking.

Preferred Skills

• Experience with AWS Glue Studio and Amazon QuickSight.
• Experience building processes for data transformation, metadata, and workload management.
• Prior experience working with federal government contracts.

Key Skills

Education

Any Gradute