Data Engineer

1. Job Purpose
Design, build, and manage the enterprise data platform that serves as the single source of truth for the entire organization. Ensure all business, manufacturing, quality, maintenance, and operational data are integrated, governed, and AI-ready to support analytics, automation, and AI Agent initiatives.
2. Key Responsibilities
Enterprise Data Platform
• Design and maintain the company's Data Lakehouse, Data Warehouse, and Manufacturing Data Hub.
• Establish a scalable enterprise data architecture capable of supporting analytics, AI, and future digital transformation initiatives.
• Develop and maintain real-time and batch data pipelines.
Manufacturing Data Integration
• Integrate data from ERP, SAP, MES, PLC, SCADA, IoT devices, Oracle databases, SharePoint, and other enterprise systems.
• Consolidate production, quality, maintenance, inventory, procurement, and finance data into a unified platform.
• Build data models that support manufacturing KPIs such as OEE, Yield, Scrap, Downtime, Throughput, and Energy Consumption.
AI Data Foundation
• Develop and manage data assets required for AI applications and AI Agents.
• Build and maintain Vector Databases, Knowledge Bases, Metadata Repositories, and AI Search Layers.
• Prepare structured and unstructured data for RAG (Retrieval-Augmented Generation) systems.
Data Governance & Quality
• Define enterprise data standards, naming conventions, and governance policies.
• Ensure data accuracy, completeness, consistency, and traceability.
• Implement automated monitoring, validation, and alerting mechanisms.
Collaboration
• Work closely with business departments to understand operational requirements and transform them into trusted data solutions.
• Support AI Agent, Analytics, and Automation teams with reliable and AI-ready datasets.