Cloud Developer, AWS - CLEARED

The Squires Group•Vienna, VA

19h•Remote

About The Position

Our client is a rapidly growing federal contractor seeking a Senior Cloud Developer. In this role, you will design, implement, and maintain secure and scalable AWS cloud infrastructure supporting a federal client's architecture. You will also develop ETL pipelines, automate deployments, manage AWS-native data services, and advance data governance and self-service analytics within a SAFe Agile environment. This role is remote, with occasional required travel to the DMV if a non-local candidate, or occasional onsite needs if a DMV local candidate. Active Secret Clearance is required per our client contract.

Requirements

Active Secret Clearance or higher.
7+ years of experience in AWS cloud development, with a focus on data engineering and DevOps.
Expertise with AWS data services, including S3, Redshift, Glue, Lake Formation, and Lambda, for developing scalable ETL pipelines and data infrastructure.
Proficiency with Data Mesh architecture and decentralized data management principles.
Strong knowledge of data governance, including data privacy, access controls, lineage, and metadata management, with experience using governance tools.
Advanced scripting skills in Python, Shell, Java, or similar languages for automation and data processing.
Experience with Infrastructure as Code (IaC) tools such as Ansible, Packer, and AWS CloudFormation for automating cloud infrastructure deployments.
Proficiency developing and managing CI/CD pipelines using Bamboo, Jenkins, or similar tools for efficient software delivery.
Expertise with monitoring and logging tools such as AWS CloudWatch, CloudTrail, Splunk, Prometheus, and Grafana for performance optimization and troubleshooting.
Strong understanding of cloud security practices, including VPC configuration, data encryption, multi-factor authentication, and AWS Security Hub integration.
Proven experience working in SAFe Agile environments using Scrum, Kanban, Jira, and Confluence for work management and documentation.
Ability to lead training on Data Mesh principles, governance practices, and analytics tools for both technical and non-technical stakeholders.
Excellent collaboration and communication skills with cross-functional data domain teams and stakeholders.

Nice To Haves

Experience with containerization technologies such as Docker, Kubernetes, or ECS for scalable data processing.
Familiarity with RESTful API development for data integration and interoperability.
Bachelor’s degree in Computer Science, Information Technology, or a related field.

Responsibilities

Participate in SAFe Agile ceremonies, including Program Increment Planning, Sprint Planning, Daily Standups, Sprint Reviews, and Retrospectives, to align development activities with strategic objectives.
Partner with Product Owners, Product Managers, and data domain teams to refine and prioritize the product backlog while maintaining alignment with Data Mesh and governance standards.
Design and deploy domain-specific data products in accordance with organizational standards for schema design, data transformations, and storage solutions.
Develop and maintain scalable ETL pipelines using AWS services such as S3, Redshift, Glue, Lake Formation, and Lambda to support self-service analytics and data domain requirements.
Implement and manage Infrastructure as Code (IaC) using tools such as Ansible, Packer, and AWS CloudFormation to automate cloud deployments and maintain configuration consistency.
Build and maintain CI/CD pipelines using tools such as Bamboo to support efficient software development and cloud deployment.
Leverage monitoring and logging tools, including AWS CloudWatch, CloudTrail, Splunk, Prometheus, and Grafana, to monitor performance, identify anomalies, and troubleshoot cloud and data infrastructure.
Apply cloud security best practices, including network security, data encryption, multi-factor authentication, and AWS Security Hub integration, to safeguard sensitive data assets.
Maintain a data catalog to improve data discoverability, lineage tracking, and transparency across data domains.
Support the operation, maintenance, and reliability of Data Mesh software while maintaining high availability.
Lead training initiatives for data stewards and users covering Data Mesh principles, governance practices, and self-service analytics tools to support organizational adoption.
Document work in Jira, including Epics, Features, and User Stories, and Confluence while maintaining detailed backlogs and transparent progress tracking.
Ensure adherence to data governance standards related to data privacy, access controls, and lineage by leveraging governance tools to automate workflows.