AI Data Engineer

Accountabilities:

• • Design, develop, test, and maintain data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources.
  • Build and optimize data architectures and models that support analytics, reporting, and operational requirements.
  • Develop AI-enabled solutions using concepts such as prompt engineering, machine learning, agentic AI, and retrieval-augmented generation (RAG).
  • Implement and manage CI/CD pipelines for data engineering workflows using Git and related development tools.
  • Develop and deploy cloud-based solutions using Azure Functions and containerization technologies such as Docker and Kubernetes.
  • Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs.
  • Develop and support RESTful and SOAP APIs and integrate data and AI/ML components into broader applications.
  • Ensure data quality and integrity through validation, monitoring, logging, and proactive issue resolution.
  • Troubleshoot and resolve production issues while maintaining high availability and reliability of data solutions.
  • Manage multiple tasks and competing priorities while delivering projects within an Agile development environment.
  • Document data flows, processes, architectures, and technical solutions to support knowledge sharing and compliance.
  • Present project status, technical work products, and complex concepts to technical and non-technical stakeholders.
  • Stay current with emerging technologies and best practices across data engineering, AI, cloud, and DevOps.

  Requirements:

  • Bachelor’s degree required.
  • 5+ years of experience in data engineering, software development, or a related technical discipline.
  • Must be able to obtain and maintain a Public Trust.
  • Hands-on experience with AI methods and tools, including prompt engineering, machine learning, agentic AI, RAG, and tools such as Copilot and Codex.
  • Strong programming experience with Java, Python, SQL, and PySpark.
  • Experience designing and developing scalable data pipelines and ETL processes.
  • Extensive experience with relational and NoSQL databases, including MySQL, PostgreSQL, SQL Server, and MongoDB, as well as stored procedure development.
  • Experience working with Databricks.
  • Experience developing and managing CI/CD pipelines using tools such as GitHub.
  • Familiarity with Git, Azure DevOps, and modern version control and collaboration practices.
  • Experience working in Agile development environments.
  • Experience with API development, including RESTful and SOAP services.
  • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.
  • Ability to work independently and manage multiple priorities in a fast-paced environment.
  • Familiarity with security best practices and compliance requirements in federal environments is preferred.
  • Experience with microservices, Spring Boot, and AI/ML component integration is advantageous.
  • Experience supporting federal programs or large-scale data modernization initiatives is a plus.
  • Previous consulting experience is preferred.

  Benefits:

  • Contract position.
  • Remote work arrangement.
  • Atlanta, Georgia is preferred, with San Antonio, Texas also listed as a preferred location.
  • Opportunity to work across data engineering, AI, machine learning, cloud, DevOps, and analytics.
  • Exposure to modern technologies including Databricks, Azure Functions, Docker, Kubernetes, PySpark, GitHub, and AI development tools.
  • Opportunity to contribute to federal programs and large-scale data modernization initiatives.
  • Cross-functional collaboration with DBAs, application developers, and other technical stakeholders.
  • Specific salary, healthcare, retirement, paid time off, and additional benefits were not specified in the source job description.