Data / Integration Engineer

About the role

We are looking for a Data / Integration Engineer to design, develop, and maintain scalable document ingestion and processing pipelines that support enterprise knowledge management and AI‑powered applications.

Key responsibilities

• Design and build multi‑stage data workflows for extracting, transforming, enriching, and indexing content from PDFs, PPTX, DOCX, CSV, and image‑based sources.
• Implement advanced document processing capabilities such as metadata extraction, content chunking, classification, summarization, and information retrieval.
• Manage vector database indexing strategies and optimize search relevance and performance.
• Develop MCP‑compatible tool servers that securely expose enterprise databases, APIs, cloud platforms, and external services to AI agents.
• Design event‑driven architectures using messaging and integration services to enable scalable, responsive data processing.
• Create and deploy data analysis, document intelligence, and knowledge retrieval agents using reusable development templates and platform tooling.
• Collaborate with cross‑functional teams to deliver reliable, innovative data engineering and AI‑driven solutions.

Required profile

• Bachelor’s degree in Computer Science, Data Engineering, IT, AI or equivalent.
• Typically 3+ years of professional experience in Python development and data pipeline engineering.
• Hands‑on experience designing and maintaining ETL/ELT workflows with orchestration platforms such as Dagster or Airflow.
• Strong proficiency with document processing frameworks for structured and unstructured data.
• Experience with vector databases, embedding models, and semantic search technologies.
• Familiarity with Azure data and AI services (Azure AI Search, Blob Storage, Event Hub, Document Intelligence).
• Proven experience developing containerized applications using Docker.
• Solid understanding of REST API design, integration patterns, and service‑oriented architectures.

Required skills

• Python
• Dagster or Airflow
• Docker
• REST API design
• Azure AI Search
• Azure Blob Storage
• Azure Event Hub
• Azure Document Intelligence
• Vector databases
• Embedding models
• Semantic search
• Document processing frameworks
• ETL/ELT workflow development
• Service‑oriented architecture