IntelliTech

Data Engineer

• Design, develop, and maintain scalable data pipelines to ingest, transform, validate, and operationalize data from a variety of enterprise sources
• Build and support data integration workflows across structured and unstructured data sources, including APIs, files, cloud storage, databases, and enterprise platforms
• Enable analytics and reporting use cases by preparing curated datasets and supporting integration with BI and analytics tools such as Tableau, Databricks, Palantir, Power BI, Qlik, or similar platforms
• Support the development of data models, transformation logic, and reusable engineering patterns that improve data access, decision support, and operational visibility
• Collaborate with analysts, engineers, and stakeholders to refine requirements and deliver data products aligned to mission needs
• Support testing, debugging, validation, and performance tuning of data pipelines and analytics workflows
• Leverage Git-based repositories and version control best practices to manage engineering efforts
• Participate in Agile development activities, including sprint planning, backlog refinement, demos, and retrospectives
• Document technical designs, data flows, transformation logic, and engineering processes to support maintainability and knowledge transfer
• Contribute to secure, scalable, and repeatable delivery practices across cloud and DevSecOps environments.

Senior Data Engineer – Analytics, BI Platforms

Full-stack Engineer

• Own overall application architecture and drive technical decisions across frontend, backend, simulation, and data tiers
• Lead sprint planning, backlog refinement, and technical prioritization in coordination with project leadership
• Conduct code reviews and enforce standards for code quality, testing, documentation, and maintainability
• Serve as a primary technical point of contact for Government engineering and product stakeholders
• Translate Government requirements and mission context into actionable engineering tasks and solution designs
• Modernize and extend a Python FastAPI backend serving as the application control plane for data operations, scenario lifecycle management, and AI orchestration
• Decouple the SimPy discrete-event simulation engine from the API tier into independently scalable worker containers
• Design and implement run request queueing, worker orchestration, and result persistence patterns
• Build governed ingestion workflows, including validation services for schema enforcement, referential integrity, circular reference detection, and business-rule validation with actionable user-facing feedback
• Implement dataset versioning, lineage tracking, and run-level traceability linking scenario outputs to explicit input versions
• Extend and maintain a React / TypeScript frontend using Material UI, Recharts, and data-grid-based visualizations
• Design and implement the AI integration layer brokering access between the application backend and a Government-approved hosted LLM endpoint
• Instrument the application pipeline to capture timing, bottleneck, concurrency, and throughput metrics
• Design and execute integration testing across frontend, backend, database, object storage, cache, and worker services.

Senior Data Engineer – Analytics, BI Platforms

Senior Data Engineer – Analytics, BI Platforms

Tech Lead – Full Stack