Data Engineer
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Key skills for this role
Role Overview
Prepare enterprise data and knowledge sources so AI, generative AI, and agentic AI solutions use accurate, current, governed, and fit-for-purpose information.
Build and maintain the pipelines and knowledge repositories that underpin retrieval-augmented AI.
Ensure AI agents draw on trusted and approved sources for business decisions.
Key Skills for This Role
Full Job Posting
Role purpose
Prepare enterprise data and knowledge sources so AI, generative AI, and agentic AI solutions use accurate, current, governed, and fit-for-purpose information.
Build and maintain the pipelines and knowledge repositories that underpin retrieval-augmented AI.
Ensure AI agents draw on trusted and approved sources for business decisions.
Data preparation for AI
- Support extraction, cleansing, classification, tagging, and indexing across structured, semi-structured, and unstructured sources.
- Build and maintain ingestion pipelines from ERP, CRM, HRMS, procurement systems, the data lake, and document repositories.
- Design chunking, metadata, and enrichment strategies to improve retrieval relevance and answer quality.
- Process PDF files, Office documents, scanned material, and email, including OCR and text extraction where required.
Knowledge repositories and RAG
- Build and maintain knowledge repositories for retrieval-augmented AI solutions.
- Generate embeddings, manage vector stores, and maintain index refresh cycles.
- Implement versioning and change detection to synchronize repositories with authoritative source systems.
- Define and apply data-layer access controls that respect entitlement and confidentiality boundaries.
- Measure and tune retrieval performance with AI engineers.
Source-listed experience
- The source metadata lists 5–8 years of experience for the role.
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