[Remote] AWS Data Engineer(only W2)

Note: The job is a remote job and is open to candidates in USA. Astir IT Solutions, Inc. is hiring an AWS Data Engineer for a remote role based in Naperville, Illinois. The role focuses on building and operating cloud data platforms on AWS, developing data ingestion and processing solutions, and implementing DevOps practices including CI/CD, infrastructure as code, monitoring, security, and production reliability.

Responsibilities

• Design and build CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy (or equivalent tools such as GitHub Actions/Jenkins) to automate build, test, and release cycles
• Provision and manage AWS cloud resources using Infrastructure as Code (Terraform), including version-controlled, reusable modules
• Containerize applications and workflows with Docker; deploy and manage containers using Amazon ECS/EKS
• Manage promotion of code and configuration across Development, Test, and Production environments with clear release and rollback strategies (blue-green/canary deployments)
• Implement secure secrets and configuration management using AWS Secrets Manager or Parameter Store, with least-privilege IAM policies
• Set up monitoring, logging, and alerting using Amazon CloudWatch (metrics, dashboards, alarms) to maintain operational visibility into pipelines and workflows
• Define and implement retry, recovery, and rerun strategies for failed jobs/workflows to ensure production reliability
• Write automation scripts (Python/Bash) for deployment, operational tasks, and routine platform maintenance
• Collaborate with data engineers, application developers, and cloud engineers to support end-to-end delivery, and troubleshoot production issues when required

Skills

• Only U.S Citizen
• B.E./B.Tech degree in Computer Science, Engineering, or a related field
• 8-10 years of overall work experience
• 5+ years of hands-on development experience building Cloud Data Platform Data Engineering solutions covering Data Ingestion, Data Quality Validations, Data Processing and Data Integration
• Strong hands-on coding experience in Python, PySpark, and SparkSQL, with solid software engineering practices including testing, version control and code reviews
• Hands-on experience in Airbyte, Snowflake and dbt
• Hands-on experience with Prefect for workflow orchestration, including designing flows and tasks, scheduling, deployments, and parameterized runs
• Ability to build reliable, observable Prefect workflows with retry logic, failure handling, and rerun/recovery support for production pipelines
• Hands-on experience with Amazon S3-based data lakes, Databricks on AWS and other AWS-based data ecosystem services
• Experience monitoring and troubleshooting orchestrated workflows via the Prefect UI/Cloud, including work pools, deployments and run history
• Demonstrated willingness and ability to set up and own DevOps practices for the platforms you build (see DevOps Skills below)
• Proficiency in analytics use-case analysis, source system analysis, and data quality assessment
• Experience coordinating/collaborating with on-shore and off-shore teams for solution delivery
• Excellent communication and presentation skills
• Design and build CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy (or equivalent tools such as GitHub Actions/Jenkins) to automate build, test, and release cycles
• Provision and manage AWS cloud resources using Infrastructure as Code (Terraform), including version-controlled, reusable modules
• Containerize applications and workflows with Docker; deploy and manage containers using Amazon ECS/EKS
• Manage promotion of code and configuration across Development, Test, and Production environments with clear release and rollback strategies (blue-green/canary deployments)
• Implement secure secrets and configuration management using AWS Secrets Manager or Parameter Store, with least-privilege IAM policies
• Set up monitoring, logging, and alerting using Amazon CloudWatch (metrics, dashboards, alarms) to maintain operational visibility into pipelines and workflows
• Define and implement retry, recovery, and rerun strategies for failed jobs/workflows to ensure production reliability
• Write automation scripts (Python/Bash) for deployment, operational tasks, and routine platform maintenance
• Collaborate with data engineers, application developers, and cloud engineers to support end-to-end delivery, and troubleshoot production issues when required
• Experience with Snowpark, and additional orchestration frameworks such as Amazon MWAA (Managed Airflow) or AWS Step Functions
• Exposure to Docker and containerized deployments; familiarity with Amazon ECS/EKS (Kubernetes) is a plus
• Experience with event-driven architectures (Amazon EventBridge, SQS, SNS, Lambda) and REST API integration across distributed services
• Exposure to Data Management principles including Data Governance, Data Cataloging, and Master Data Management
• Exposure to cloud-native MDM tooling
• Exposure to BI analytics using Amazon QuickSight

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