Full Stack Data Engineer | Cloud Infrastructure, ETL & AI-Enabled Analytics | Active TS/SCI with Full Scope Poly Required
Are you a highly skilled Full Stack Data Engineer with deep expertise across cloud platforms, data pipeline automation, and modern application development? We are looking for a technically versatile, mission-focused professional ready to architect and deliver sophisticated data engineering and analytics solutions in direct support of a high-profile intelligence community program.
WHAT YOU'LL DO
As a Full Stack Data Engineer, you will be a core technical contributor responsible for building, automating, and sustaining the cloud-based data infrastructure and applications that power analytical missions. You will design and manage complex SQL databases, engineer and automate ETL pipelines using NiFi and Python, and develop user-centered web applications — all within a secure, cloud-native environment. You will optimize connectivity between cloud services and high-performance on-premises compute, maintain robust CI/CD pipelines, and ensure systems are thoroughly documented and architecturally sound. From provisioning AWS cloud resources and deploying containerized applications to supporting data scientists in fine-tuning AI models, your contributions will span the full data and application stack — making a direct, measurable impact on mission outcomes.
WHAT WE'RE LOOKING FOR
Required Qualifications:
- Clearance: Active Top Secret/SCI clearance with Full Scope Polygraph (FS Poly) required — candidates without an active clearance will not be considered
- Education: Bachelor's or Master's Degree in Computer Science, Computer Engineering, Systems Engineering, or a related field preferred
- Experience: Demonstrated professional experience in full stack data engineering, application development, and cloud infrastructure management
Required Technical Skills:
- Application Development: Demonstrated experience developing, customizing, and deploying applications in support of analytical missions and intelligence-driven use cases
- Cloud Services & Infrastructure: Hands-on experience with AWS cloud services including S3, RDS, and EC2, as well as provisioning and managing cloud compute resources across AWS, Azure, or comparable platforms
- SQL & Database Management: Expert-level experience managing relational SQL databases (MySQL and PostgreSQL) in cloud environments, including schema creation, cross-database mapping, and streamlining data discovery
- ETL Engineering: Proven experience implementing and automating NiFi workflows for Extract-Transform-Load (ETL) processes, including custom Python or Java development and OS-level scripting for ETL operations on SQL databases
- CI/CD Pipeline Management: Demonstrated experience building and maintaining CI/CD pipelines using Git/GitHub, Jenkins, Jira, and Confluence across the full software development lifecycle
- Containerization: Hands-on experience with Docker and containerized application and database deployment in cloud-based environments
- Frontend Development: Proficiency in JavaScript, CSS, HTML5, and Flask, with a strong understanding of user-centered design principles, web standards, typography, and usability best practices
- Coding Proficiency: Professional proficiency in SQL, PL/SQL, Python, and Java across data engineering and application development contexts
- Development Tooling: Demonstrated experience with Anaconda, Bash, and Terraform for development, automation, and infrastructure provisioning
- Automated Testing & Deployment: Experience with automated testing and infrastructure-as-code deployment approaches to ensure reliability and consistency across environments
- Cloud-to-On-Prem Connectivity: Demonstrated experience optimizing connectivity between cloud-based services and on-premises high-performance compute servers
- Systems Documentation: Proven ability to create and maintain comprehensive systems and architectural documentation for both technical and stakeholder audiences
- Version Control: Proficiency with Git for version control and collaborative development workflows
NICE TO HAVE
Preferred Qualifications:
- AI & Machine Learning Support: Experience supporting data scientists in developing AI models through fine-tuning and transfer learning for classification, prediction, generative AI, or similar tasks
- AI Model Deployment: Hands-on experience optimizing the deployment and performance of AI/ML models in cloud environments
- Data Visualization: Experience connecting cloud servers to Tableau or similar platforms to deliver actionable visual analytics outputs
- Distributed Computation: Experience with distributed computing frameworks and designing parallel processing solutions for large-scale data workloads
- Sponsor Mission Experience: Prior experience working in a Sponsor analytic mission area, including research on analyst user needs and data management lifecycle support
- Complex Problem Structuring: Demonstrated ability to organize and structure solutions to complex, multi-faceted technical problems clearly and effectively
- Prioritization Under Pressure: Proven ability to balance competing priorities and deliver high-quality results across multiple concurrent workstreams in a fast-paced environment
- Coordination & Collaboration: Strong cross-functional coordination skills with a track record of effective stakeholder engagement and team-based delivery
i270 Solutions Group LLC., is an Equal Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law.