Senior Data Engineer

Headquartered in Abu Dhabi, United Arab Emirates, the organization specializes in developing AI-powered supply chain solutions that integrate fragmented SAP, Ariba, and unstructured data into actionable intelligence. The company focuses on architecting ultra-secure data lake houses to deliver real-time analytics, secure high-performance pipelines, and enable advanced generative AI applications, supporting critical enterprise workflows and procurement automation in defense and technical sectors.

We are seeking a Senior Data Engineer to architect and develop the core data infrastructure that will underpin our AI-driven transformation. In this pivotal role, you will move beyond traditional ETL processes to design and deploy high-security Data Lakehouse environments, establishing a single, authoritative source of truth for our AI systems. You will lead the technical implementation of "Workstream 1:
Data & Platform Foundations," a critical initiative for our flagship projects. Your responsibilities will include integrating complex enterprise systems such as SAP S/4

HANA and Ariba, as well as processing unstructured data like technical drawings and regulatory documents. By collaborating across teams, you will build high-performance pipelines and systems that power Intelligent Supply Chain forecasting and generative AI tools. Operating within a structured "Sprint Zero" framework, you will ensure robust data lineage, security, and compliance with defense-grade standards. This role demands expertise in both structured and unstructured data engineering, with a focus on creating scalable, secure, and high-performance data architectures.

Your work will directly enable AI agents to optimize procurement processes and support engineers in developing next-generation systems, making you instrumental in transforming raw data into a strategic advantage for national defense capabilities.

• Design and deploy defense-grade Data Lakehouse architectures to serve as the Single Source of Truth for AI-driven Supply Chain Intelligence, ensuring high-performance pipelines and systems for Intelligent Supply Chain forecasting and generative AI tools.
• Lead the technical execution of Workstream 1:
  Data & Platform Foundations, mapping rigid enterprise systems (e.g., SAP S/4
  
  HANA, Ariba) and collaborating with cross-functional teams to integrate and process complex unstructured data (technical drawings, regulatory text) for AI applications.
• Architect and deploy ingestion pipelines to extract high-volume transactional data from ERP systems like SAP S/4
  
  HANA, Ariba, and PLM, ensuring near real-time availability for forecasting models and AI agents.
• Build connectors for external market intelligence feeds (e.g., S&P Global, Orbis, Eco Vadis) to enrich internal procurement data with macroeconomic and geopolitical signals for enhanced decision-making.
• Design and implement a standardized procurement data model and taxonomy across multiple entities, harmonizing fragmented datasets into a cohesive analytics layer.
• Engineer pipelines to ingest, process, and transform unstructured technical data (PDF tender documents, CAD metadata, historical CONOPS) into vector-ready formats for Retrieval-Augmented Generation (RAG) applications.
• Manage and optimize Vector Databases (e.g., Weaviate) to store embeddings of archival proposals and engineering snippets, ensuring high-speed retrieval for AI drafting assistants and generative tools.
• Establish data lineage and traceability protocols to link requirements to physical components, supporting Model-Based Systems Engineering (MBSE) and the Digital Thread implementation.
• Implement Role-Based Access Control (RBAC), audit logging, and data redaction policies to ensure compliance with export controls and strict on-premise security requirements.
• Deploy automated data quality frameworks to validate Bill of Materials (BOM) completeness and cost data accuracy before ingestion into AI models.
• Optimize data pipelines for on-premise GPU clusters and air-gapped environments, ensuring efficiency and performance within existing infrastructure constraints.
• Operate within a structured Sprint Zero…