Software Engineer SME (TS/SCI with Poly Required)

GCI Incorporated•McLean, VA

About The Position

GCI embodies excellence, integrity and professionalism. The employees supporting our customers deliver unique, high-value mission solutions while effectively leverage the technological expertise of our valued workforce to meet critical mission requirements in the areas of Data Analytics and Software Development, Engineering, Targeting and Analysis, Operations, Training, and Cyber Operations. We maximize opportunities for success by building and maintaining trusted and reliable partnerships with our customers and industry. At GCI, we solve the hard problems. As a Software Engineer, a typical day will include the following duties: Process through NiFi schemas or custom scripts large datasets into Customer's on-premise and Cloud environments through the development of algorithms and schemas analyzing new data sets to optimize this ingestion. Generate metrics to track data ingest statistics to maintain data integrity. Document the data-flows according to standards set by Customer. Complete all steps in the product-design process from conceptualization, detailed user interface, functional design, through implementation and usability review. Develop conceptual models, workflows, design prototypes, and user interface specifications. Lead work to optimize cloud-based computing technologies, such as leveraging pyspark, distributed computation, and model training or inference, and integrate solutions into relevant delivery mechanisms or partner systems. Build tools and scripts to monitor, troubleshoot, automate, and deploy Al models and outputs as part of a variety of existing business analytic platforms. Directly responsible for solutions related to the Customer's analytic work in these key areas: availability, latency, performance, efficiency, documentation, change management, monitoring, security, emergency response, and capacity planning. Apply, develop and deploy cloud microservices and integration of cloud resources with on prem high performance computation servers to support the Customer's efforts. Use the Customer's knowledge management, version control, coding standards, and delivery platforms. Champion and manage requirements, builds, upgrades, and fixes within multiple (dev, test, production) environments. Assist developers and data scientists with code deployments, particularly providing Cl/CD configuration. Use a microservice-based architecture and agile coding for engineering and development activities to support reliable network performance, modern resource management, and security processes. Provide engineering services to the Customer's data science team to maximize the data scientist's effectiveness including the preparation of data science compute environments, data engineering, data modeling, data triage, database support and administration, backend and UX development, product evaluation, analytical support, operational support, bag data analytics scale-out design, and knowledge management. Design coherent architectures for platforms that enable the collection, analysis, and visualization of multiple types of data. Recommend improvements to databases, applications, and processes to support near real-time insights and integration into business processes.

Requirements

Demonstrated experience in the development, customization, and use of developing applications for analysis.
Demonstrated experience with cloud microservices and tools, such as S3, RDSes, and EC2 instances.
Demonstrated experience managing Structured Query Language (SQL) databases within cloud based relational databases; specifically, populating SQL database (MySQL and Postgres) with new schemas, mapping between different SQL databases, and streamlining data discovery.
Demonstrated experience implementing and automating Nifi workflows for Extract-Transform load processes, as well as custom Python or Java code when appropriate.
Demonstrated experience creating operating system level scripts to perform ETL operations on SQL databases.
Demonstrated experience with version control systems, specifically Git.
Demonstrated experience with JavaScript, CSS, HTMLS, and Flask.
Demonstrated experience using containerization such as Docker or developing and deploying containerized applications or databases.
Demonstrated experience with user-centered design principles and practices, web standards, typography and color, and web usability standards.
Demonstrated experience Anaconda, Bash, and Terraform for development purposes.
Demonstrated experience building and maintaining Cl/CD pipelines with software such as source control (Git/GitHub), continuous build/delivery (Jenkins), issue management (Jira), and documentation/collaboration (Confluence).
Demonstrated experience with automated testing and deployment of infrastructure or configurations.
Demonstrated experience in the administration, provisioning, and use of cloud technologies (i.e. AWS) particularly with application of data science approaches in the cloud.
Demonstrated experience optimizing connectivity between cloud-based services and on prem high performance cloud compute servers.
Demonstrated experience creating and maintaining systems and architectural documentation.
Demonstrated experience with provisioning and management of cloud compute resources and services, such as AWS, Azure, or similar.
Demonstrated professional proficiency with the following coding languages: SQL, PL/SQL, Python, Java.
A candidate must be a US Citizen and requires an active/current TS/SCI with Polygraph clearance.

Nice To Haves

Demonstrated experience in Computer Science, Computer Engineering, Systems Engineering, or closely related discipline.
Demonstrated experience organizing and structuring solutions to complex problems.
Demonstrated strong coordination and collaboration skills.
Demonstrated experience working in a Customer analytic mission area, specifically involving research on analyst user needs.
Demonstrated experience supporting data scientists to create-through fine tuning, transfer learning-models for classification, prediction, generative Al, or other similar tasks.
Demonstrated experience optimizing the deployment of Al models in the cloud.
Demonstrated experience connecting cloud servers to Tableau to output visualizations.
Demonstrated experience with the Customer's data management lifecycle.
Demonstrated experience balancing competing activities and priorities.
Demonstrated experience with distributed computation, including experience creating parallel processing solutions.

Responsibilities

Process through NiFi schemas or custom scripts large datasets into Customer's on-premise and Cloud environments through the development of algorithms and schemas analyzing new data sets to optimize this ingestion.
Generate metrics to track data ingest statistics to maintain data integrity.
Document the data-flows according to standards set by Customer.
Complete all steps in the product-design process from conceptualization, detailed user interface, functional design, through implementation and usability review.
Develop conceptual models, workflows, design prototypes, and user interface specifications.
Lead work to optimize cloud-based computing technologies, such as leveraging pyspark, distributed computation, and model training or inference, and integrate solutions into relevant delivery mechanisms or partner systems.
Build tools and scripts to monitor, troubleshoot, automate, and deploy Al models and outputs as part of a variety of existing business analytic platforms.
Directly responsible for solutions related to the Customer's analytic work in these key areas: availability, latency, performance, efficiency, documentation, change management, monitoring, security, emergency response, and capacity planning.
Apply, develop and deploy cloud microservices and integration of cloud resources with on prem high performance computation servers to support the Customer's efforts.
Use the Customer's knowledge management, version control, coding standards, and delivery platforms.
Champion and manage requirements, builds, upgrades, and fixes within multiple (dev, test, production) environments.
Assist developers and data scientists with code deployments, particularly providing Cl/CD configuration.
Use a microservice-based architecture and agile coding for engineering and development activities to support reliable network performance, modern resource management, and security processes.
Provide engineering services to the Customer's data science team to maximize the data scientist's effectiveness including the preparation of data science compute environments, data engineering, data modeling, data triage, database support and administration, backend and UX development, product evaluation, analytical support, operational support, bag data analytics scale-out design, and knowledge management.
Design coherent architectures for platforms that enable the collection, analysis, and visualization of multiple types of data.
Recommend improvements to databases, applications, and processes to support near real-time insights and integration into business processes.