Job Description

BT-127 – Data Engineer
Skill Level: Subject Matter Expert
Location: McLean (fully on-site, no remote option)

 

**MUST HAVE A POLY CLEARANCE TO APPLY. Those without a Poly clearance will not be considered.**

• The Candidate shall work with data scientists and data engineers to architect, operate, and document relevant cloud-on prem hybrid solutions to optimize relevant workflow components for advanced artificial intelligence applications.
• The Candidate shall lead work to optimize cloud-based computing technologies, such as leveraging pyspark, distributed computation, and model training/inference, and integrate solutions into relevant delivery mechanisms or partner systems.
• The Candidate shall build tools and scripts to monitor, troubleshoot, automate, and deploy AI models and outputs as part of a variety of existing business analytic platforms.
• The Candidate shall be directly responsible for solutions related to analytic work in these key areas: availability, latency, performance, efficiency, documentation, change management, monitoring, security, emergency response, and capacity planning.
• The Candidate shall apply, develop and deploy cloud microservices and integration of cloud resources with on prem high performance computation servers to support efforts.
• The Candidate shall create and use optimal solutions to store and host information.
• The Candidate shall create software pipelines to query databases of interest, combine and merge data sources, and analyze information.
• The Candidate shall use knowledge management, version control, coding standards, and delivery platforms.
• The Candidate shall champion and manage requirements, builds, upgrades, and fixes within multiple (dev, test, production) environments.
• The Candidate shall assist developers and data scientists with code deployments, particularly providing CI/CD configuration.
• The Candidate shall leverage available solutions to create automations that enable timely tipping and queuing.
• The Candidate shall optimize open-source software to accelerate solutions and minimize proprietary dependencies.
• The Candidate shall use a microservice-based architecture and agile coding for engineering and development activities to support reliable network performance, modern resource management, and security processes.
• The Candidate shall develop analytical software packages, pipelines, and custom virtual environments for deployment in secure environments including standalone workstations, standalone compute clusters, secure cloud environments, and on-premises network infrastructure.

1. Demonstrated experience with Python, Bash, and Terraform.
2. Demonstrated experience Anaconda for development purposes.
3. Demonstrated experience building and maintaining CI/CD pipelines with software such as source control (Git/GitHub), continuous build/delivery (Jenkins), issue management (Jira), and documentation/collaboration (Confluence).
4. Demonstrated experience with automated testing and deployment of infrastructure or configurations.
5. Demonstrated experience in the administration, provisioning, and use of cloud technologies (i.e. AWS) particularly with application of data science approaches in the cloud.
6. Demonstrated experience deploying and tuning Apache NiFi or other ETL workflows.
7. Demonstrated experience hosting and managing Structured Query Language (SQL) databases within cloud based relational databases.
8. Demonstrated experience optimizing connectivity between cloud-based services and on prem high performance cloud compute servers.
9. Demonstrated experience with DevSecOps solutions and tools.
10. Demonstrated experience in the cyber security domain to include: governance and risk management, compliance, encryption, software development security, access control, network security or secure architecture, or security operations.
11. Demonstrated experience preparing presentations and presenting to senior stakeholders.

1. Demonstrated experience supporting data scientists to create—through fine tuning, transfer learning—models for classification, prediction, generative AI, or other similar tasks.
2. Demonstrated experience optimizing the deployment of AI models in the cloud.
3. Demonstrated experience with front-end web development frameworks such as Flask.
4. Demonstrated experience using Tableau to connect cloud serves to Tableau output visualizations.

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