Data Engineer - AI 30-35K
Summary
The Data Engineer will design and maintain end-to-end data pipelines, infrastructure, and RAG solutions to support AI and analytics initiatives. The role involves working with structured, unstructured, and vector data within a large-scale corporate environment.
- Design and deliver end-to-end data solutions covering validation, transformation, and retrieval.
- Handle diverse data types including structured, unstructured, and vector data.
- Build, deploy, and maintain data infrastructure within project scope.
- Develop and manage ETL pipelines and data schemas to support analytics and AI use cases.
- Implement and support data operations using notebooks and automation tools.
- Enable and maintain RAG solutions for LLM-based applications.
- Provide data engineering expertise and support to non-technical stakeholders.
- Ensure data reliability, performance, and scalability across platforms.
- Design and deliver end-to-end data solutions covering validation, transformation, and retrieval.
- Handle diverse data types including structured, unstructured, and vector data.
- Build, deploy, and maintain data infrastructure within project scope.
- Develop and manage ETL pipelines and data schemas to support analytics and AI use cases.
- Implement and support data operations using notebooks and automation tools.
- Enable and maintain RAG solutions for LLM-based applications.
- Provide data engineering expertise and support to non-technical stakeholders.
- Ensure data reliability, performance, and scalability across platforms.
Work on modern data platforms and GenAI-driven solutionsHands-on exposure to RAG, Spark, and cloud data engineering
Our client is a well-established organization within the business services industry, recognized for its commitment to innovation and excellence. They are a large organization with a global presence and a focus on leveraging technology to drive business success.
- Competitive monthly salary and benefits package.
- Exposure to cutting-edge technology and tools within the technology department.
- Collaborative and inclusive work environment.
- Chance to contribute to impactful projects and enhance your data engineering expertise.