J
RemoteFull-timeMid levelIT
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$137K–$240K/yr
Estimate — the employer hasn't published pay.
Based on 906 similar mid-level Software Engineering jobs in United States that show pay. The range is the middle half of their posted pay (25th to 75th percentile), not an offer — ask the employer for the real range.
Software Engineering salaries →This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Developer, AWS - CLEARED based in United States.
This is a senior cloud development role focused on building secure, scalable AWS infrastructure and data solutions for a federal environment. You will develop cloud-native data products, scalable ETL pipelines, automated deployments, and self-service analytics capabilities. The role combines AWS development, data engineering, DevOps, infrastructure automation, and data governance within a SAFe Agile environment. You will work closely with product leaders and data domain teams to implement Data Mesh principles and deliver reliable, governed data products. Security, observability, automation, and high availability are central to the role, with responsibility for protecting sensitive federal data assets. The position is fully remote, with occasional travel to the DMV area and potential onsite needs depending on location and project requirements. An active Secret Clearance or higher is required.
Participate in SAFe Agile ceremonies, including Program Increment Planning, Sprint Planning, Daily Standups, Sprint Reviews, and Retrospectives, to coordinate development activities and maintain alignment with program objectives.
Partner with Product Owners, Product Managers, and data domain teams to refine and prioritize backlogs while ensuring alignment with Data Mesh and data governance standards.
Design and deploy domain-specific data products using established standards for schemas, data transformations, storage, and decentralized data management.
Develop and maintain scalable ETL pipelines using AWS services such as S3, Redshift, Glue, Lake Formation, and Lambda.
Implement Infrastructure as Code using Ansible, Packer, AWS CloudFormation, and related tools to automate deployments and maintain consistent cloud configurations.
Build and maintain CI/CD pipelines using Bamboo, Jenkins, or comparable technologies to support efficient and reliable software delivery.
Monitor cloud and data infrastructure using AWS CloudWatch, CloudTrail, Splunk, Prometheus, Grafana, and other observability tools to identify anomalies, optimize performance, and troubleshoot issues.
Apply cloud security best practices, including VPC configuration, encryption, multi-factor authentication, and AWS Security Hub integration, to protect sensitive data and infrastructure.
Maintain data catalogs that improve data discoverability, lineage, metadata transparency, and understanding across data domains.
Support the operation, maintenance, reliability, and high availability of Data Mesh software and associated cloud services.
Lead training and knowledge-sharing initiatives for data stewards and users covering Data Mesh concepts, governance practices, and self-service analytics tools.
Maintain detailed documentation and project tracking in Jira and Confluence, including Epics, Features, User Stories, backlogs, and delivery progress.
Ensure data governance requirements related to privacy, access controls, metadata, and lineage are consistently implemented and supported through automated workflows.
Collaborate with cross-functional technical and business stakeholders to resolve challenges and continuously improve cloud, data, and governance capabilities.
Hold an active Secret Clearance or higher.
Bring 7+ years of experience in AWS cloud development, with a strong focus on data engineering and DevOps.
Demonstrate advanced expertise with AWS data services, including S3, Redshift, Glue, Lake Formation, and Lambda, for scalable ETL pipelines and data infrastructure.
Have strong knowledge of Data Mesh architecture and decentralized data management principles.
Demonstrate practical experience with data governance, including privacy, access controls, data lineage, metadata management, and governance tooling.
Possess advanced scripting skills in Python, Shell, Java, or comparable programming languages for automation and data processing.
Have hands-on experience with Infrastructure as Code tools such as Ansible, Packer, and AWS CloudFormation.
Demonstrate proficiency building and managing CI/CD pipelines with Bamboo, Jenkins, or similar platforms.
Have strong experience with monitoring and logging technologies such as AWS CloudWatch, CloudTrail, Splunk, Prometheus, and Grafana.
Possess a solid understanding of cloud security practices, including VPC configuration, data encryption, multi-factor authentication, and AWS Security Hub.
Have experience working in SAFe Agile environments using Scrum, Kanban, Jira, and Confluence.
Be capable of leading training on Data Mesh principles, governance practices, and analytics tools for both technical and non-technical audiences.
Demonstrate excellent communication, collaboration, and stakeholder-management skills across cross-functional data teams.
Experience with containerization technologies such as Docker, Kubernetes, or ECS is preferred.
Familiarity with RESTful API development for data integration and interoperability is preferred.
A Bachelor's degree in Computer Science, Information Technology, or a related field is preferred.
Salary of up to $150,000 USD, based on experience, qualifications, location, and certifications.
Fully remote position within the United States.
Occasional travel to the DMV area may be required for non-local candidates, with potential onsite needs for local DMV candidates.
Opportunity to work on secure cloud and data solutions supporting a federal client environment.
Hands-on experience across AWS cloud development, data engineering, DevOps, Data Mesh, and self-service analytics.
Exposure to AWS services including S3, Redshift, Glue, Lake Formation, Lambda, CloudWatch, CloudTrail, and Security Hub.
Opportunity to contribute to cloud security, data governance, automation, and high-availability initiatives.
Collaboration with product leaders, data domain teams, and cross-functional stakeholders.
Leadership and training opportunities focused on Data Mesh, governance, and analytics adoption.
Referral program opportunities.