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AI Data Engineer

๐Ÿ•’ 4 days ago
Data EngineeringAI SolutionsETL ProcessesSQL

๐Ÿ“œ Description

  • Design, develop, test and maintain data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources (SQL, R, Python).
  • Build and optimize data architectures and models to support analytics, reporting, and operational needs.
  • Implement and manage CI/CD pipelines for data engineering workflows using tools such Git.
  • Develop and deploy cloud-based solutions leveraging Azure Functions, and containerization (Docker, Kubernetes).
  • Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs.

๐Ÿ› ๏ธ Requirements

  • Must be able to OBTAIN and MAINTAIN a 'PUBLIC TRUST'.
  • A bachelor's degree is required.
  • FIVE (5) years of experience in data engineering, software development, or related roles.
  • Experience with Co-Pilot and CodeX, and AI methods.
  • Experience in programming languages and technologies, including Java, Python, SQL, and PySpark, as well as API development (RESTful and SOAP).
  • Experience designing and developing data pipelines and ETL processes.
  • Extensive experience with relational and NoSQL databases, such as MySQL, PostgreSQL, SQL Server, and MongoDB, including stored procedure development.
  • Experience working with Databricks.
  • AI experience with prompt engineering, machine learning, agentic AI and RAG concepts.
Full job description

Client seeks a Data Engineer with some AI experience to support in building, optimizing, and maintaining data pipelines, AI solutions, and analytics platforms. The ideal candidate will have hands-on experience with modern data engineering tools, AI solutions, CI/CD, and version control, and will collaborate with cross-functional teams to deliver high-quality, scalable data solutions.

  • AI experience with prompt engineering, machine learning, agentic AI and RAG concepts
  • Design, develop, test and maintain data pipelines and ETL processes for ingesting, transforming, and loading data from diverse sources (SQL, R, Python).
  • Build and optimize data architectures and models to support analytics, reporting, and operational needs.
  • Implement and manage CI/CD pipelines for data engineering workflows using tools such Git.
  • Develop and deploy cloud-based solutions leveraging Azure Functions, and containerization (Docker, Kubernetes).
  • Collaborate with DBAs and application developers to design and integrate data models, stored procedures, and APIs.
  • Ensure data quality and integrity through validation, monitoring, and logging.
  • Manage multiple tasks effectively across competing priorities.
  • Troubleshoot and resolve issues in production environments, ensuring high availability and reliability.
  • Document data flows, processes, and technical solutions for knowledge sharing and compliance.
  • Stay current with emerging technologies and best practices in data engineering, cloud, and DevOps.


What You Will Need:

  • Must be able to OBTAIN and MAINTAIN a "PUBLIC TRUST".
  • A bachelorโ€™s degree is required.
  • FIVE (5) years of experience in data engineering, software development, or related roles.
  • Experience with Co-Pilot and CodeX., and AI methods.
  • Experience presenting status and work products.
  • Experience in programming languages and technologies, including Java, Python, SQL, and PySpark, as well as API development (RESTful and SOAP).
  • Experience designing and developing data pipelines and ETL processes.
  • Extensive experience with relational and NoSQL databases, such as MySQL, PostgreSQL, SQL Server, and MongoDB, including stored procedure development.
  • Experience working with Databricks.
  • Experience with CI/CD tools and pipelines, such as GitHub.
  • Experience operating in Agile development environments.


What Would Be Nice To Have:

  • Experience supporting federal programs and/or large-scale data modernization projects.
  • Familiarity with version control and collaboration tools, including Git, and Azure Dev Ops
  • Ability to work independently in a fast-paced environment.
  • Strong analytical and troubleshooting skills.
  • Excellent verbal and written communication skills, with the ability to clearly communicate complex technical concepts to diverse audiences.
  • Familiarity with containerization and orchestration technologies
  • Familiarity with security best practices and compliance in federal environments.
  • Experience with microservices, Spring Boot, and integration of AI/ML components.
  • Previous consulting experience

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