Software Development Engineer TS/SCI POLY CLEARED

• Develop algorithms, schemas, and custom solutions to process and ingest large datasets into cloud and on-premises environments.
• Design, implement, and optimize data ingestion workflows using Apache NiFi, custom Python scripts, and other ETL technologies.
• Generate and maintain metrics to monitor data ingest performance, quality, and integrity.
• Create and maintain technical documentation, data flow diagrams, and system architecture documentation.
• Participate in the full product development lifecycle, including requirements gathering, design, implementation, testing, and deployment.
• Develop conceptual models, workflows, user interface designs, and functional specifications.
• Optimize cloud-based computing technologies through distributed processing, PySpark, machine learning model training, and model deployment.
• Build automation tools and scripts to monitor, troubleshoot, deploy, and maintain AI/ML models and analytics platforms.
• Support cloud infrastructure performance, availability, scalability, security, monitoring, and capacity planning initiatives.
• Develop cloud-native microservices and integrate cloud resources with on-premises high-performance computing environments.
• Utilize Sponsor-approved version control systems, coding standards, knowledge management tools, and delivery platforms.
• Manage software builds, upgrades, patches, and deployments across development, testing, and production environments.
• Support developers and data scientists through CI/CD implementation and deployment automation.
• Apply Agile development methodologies and microservice architectures to improve system performance, resource management, and security.
• Provide engineering support for data science teams, including compute environment preparation, data engineering, database administration, backend development, operational support, and knowledge management.
• Design enterprise architectures supporting the collection, analysis, and visualization of diverse data sources.
• Recommend enhancements to databases, applications, and processes to enable near real-time analytics and improved business outcomes.
• Additional duties may be assigned.

The ideal candidate will possess strong expertise in cloud technologies, data engineering, DevOps, automation, and software development, with a passion for building innovative solutions that enable advanced analytics and data science capabilities., * Bachelor’s degree in Computer Science, Computer Engineering, Systems Engineering, Information Technology, or a related technical field.

• Active TS/SCI clearance with Polygraph required.
• Demonstrated experience developing applications supporting large-scale data analysis.
• Experience with cloud services and architectures, including AWS technologies such as S3, RDS, and EC2.
• Experience administering and optimizing SQL databases, including MySQL and PostgreSQL.
• Experience implementing ETL workflows using Apache NiFi and custom Python or Java solutions.
• Experience creating operating system-level scripts to automate data processing tasks.
• Experience on SELinux and Ansible automation
• Experience using Git and version control best practices.
• Experience with JavaScript, HTML5, CSS, Flask, and modern web development technologies.
• Experience developing and deploying containerized applications using Docker or similar technologies.
• Experience applying user-centered design principles and web usability standards.
• Experience using Anaconda, Bash, and Terraform for development and infrastructure automation.
• Experience building and maintaining CI/CD pipelines utilizing tools such as GitHub, Jenkins, Jira, and Confluence.
• Experience with automated testing, infrastructure deployment, and configuration management.
• Experience provisioning and managing cloud infrastructure, including AWS, Azure, or similar cloud platforms.
• Experience integrating cloud-based services with on-premises high-performance computing environments.
• Strong documentation and system architecture experience.
• Professional proficiency in SQL, PL/SQL, Python, and Java., * Advanced experience in Computer Science, Computer Engineering, Systems Engineering, or related disciplines.
• Experience supporting data scientists in machine learning model development, transfer learning, fine-tuning, and generative AI initiatives.
• Experience deploying and optimizing AI/ML models in cloud environments.
• Experience integrating cloud-based analytics platforms with Tableau visualization tools.
• Experience supporting data management lifecycles within intelligence or analytics organizations.
• Experience designing distributed computing and parallel processing solutions.
• Strong analytical problem-solving skills.
• Excellent collaboration and stakeholder engagement abilities.
• Experience conducting user research and supporting analytical mission environments.
• Ability to effectively balance multiple competing priorities and deadlines.

• 401(k) matching
• Dental insurance
• Employee assistance program
• Health insurance
• Health savings account
• Paid time off
• Retirement plan
• Vision insurance