AI Data Engineer
New
J
JobgetherData engineering, AI
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Data Engineer based in United States.ContractMiddle
Salary not disclosed
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Job Details
- Experience
- 5+ years of experience in data engineering, software development, or a related technical discipline.
- Required Skills
- PythonSQLETLJavaKubernetesMachine LearningRESTful APIsDatabricksPrompt EngineeringPySpark
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 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.
- Experience with relational and NoSQL databases, including MySQL, PostgreSQL, SQL Server, and MongoDB, and with stored procedure development.
- Experience working with Databricks and developing and managing CI/CD pipelines using tools such as GitHub.
- Familiarity with Git, Azure DevOps, Agile development environments, Docker, and Kubernetes.
- Experience with API development, including RESTful and SOAP services.
- Strong analytical, troubleshooting, and problem-solving skills; ability to work independently and manage multiple priorities.
Responsibilities
- Design, develop, test, and maintain data pipelines and ETL processes for diverse data sources.
- Build and optimize data architectures and models for analytics, reporting, and operational needs.
- Develop AI-enabled solutions using prompt engineering, machine learning, agentic AI, and retrieval-augmented generation.
- Implement and manage CI/CD pipelines for data engineering workflows using Git and related tools.
- Develop and deploy cloud-based solutions using Azure Functions, Docker, and Kubernetes.
- Collaborate with DBAs and application developers on data models, stored procedures, and APIs.
- Develop and support RESTful and SOAP APIs and integrate data and AI/ML components into applications.
- Monitor data quality and integrity, troubleshoot production issues, and maintain solution reliability.
- Document data flows, processes, architectures, and technical solutions; present technical work and project status to stakeholders.
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