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Role: AWS Data Engineer
Location: Remote
Duration: Long Term Contract/Full-time
Job Summary
Client is seeking a Senior AWS Data Engineer to support a large-scale CMS data and analytics platform. This role will be responsible for designing, building, and optimizing cloud-native data pipelines and analytics solutions within AWS, enabling the collection, transformation, and delivery of critical healthcare data used for reporting, analysis, and decision-making. The ideal candidate will have deep experience with AWS data services, modern ETL frameworks, cloud-based data lakes, and large-scale data processing. The individual will work closely with data architects, business analysts, application teams, and CMS stakeholders to deliver scalable and secure solutions supporting healthcare and federal data initiatives.
Responsibilities
Design, develop, and maintain scalable AWS-based data pipelines and ETL processes.
Build and optimize data ingestion, transformation, and enrichment workflows using AWS Glue, PySpark, Python, and SQL.
Develop and maintain cloud-native data lake and warehouse solutions leveraging Amazon S3, Redshift, Athena, and other AWS services.
Design and implement data models that support analytics, reporting, and operational use cases.
Integrate data from multiple structured and unstructured data sources.
Support the development of dashboards and reporting solutions using Amazon QuickSight and other business intelligence tools.
Collaborate with architects and stakeholders to define data requirements, business rules, and data governance standards.
Implement automated testing, monitoring, and performance optimization for data pipelines.
Ensure compliance with CMS, federal, and organizational security requirements.
Support CI/CD and Infrastructure as Code (IaC) practices utilizing Terraform, CloudFormation, and Git-based workflows.
Troubleshoot data quality, performance, and production issues across cloud environments.
Participate in Agile ceremonies and contribute to technical design discussions.
Required Qualifications
7+ years of experience in data engineering, cloud engineering, or related technical roles.
5+ years of hands-on AWS experience in production environments.
Strong proficiency with: Python, SQL, PySpark, AWS Glue, Amazon S3, Amazon Athena Amazon Redshift
Experience building enterprise ETL and ELT solutions.
Experience designing and implementing cloud-native data architectures.
Strong understanding of data warehousing and dimensional modeling concepts.
Experience with Infrastructure as Code using Terraform and/or CloudFormation.
Experience working with Git, CI/CD pipelines, and DevOps practices.
Familiarity with container technologies including Docker and Kubernetes.
Strong analytical, troubleshooting, and problem-solving skills.
Excellent verbal and written communication skills.
Preferred Qualifications
Previous experience supporting CMS or other Federal Health agencies.
Experience working with Medicare, Medicaid, healthcare, claims, or beneficiary datasets.
Experience with AWS GovCloud environments.
Experience with Amazon QuickSight development, dashboards, datasets, SPICE, and Direct Query.
Experience with Databricks or Apache Spark platforms.
Knowledge of cloud security and access controls including IAM, KMS, and Secrets Manager.
Experience supporting large-scale analytics or data modernization initiatives.
AWS Certified Data Engineer, Solutions Architect, or related AWS certification.
Nice-to-Have Experience
Medicaid Enterprise Systems
Healthcare interoperability initiatives
Data governance and master data management
Work arrangement
Yes
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