Data Engineer / Architect

We are looking for a Data Engineer or Integration Architect with strong experience in data integration, system connectivity, and data transformation, preferably with exposure to PIM (Product Information Management) and product data ecosystems. The role involves designing scalable, reusable, and stateless integration solutions to connect PIM and enterprise source systems with downstream platforms such as e-commerce, search, BI, and analytics. The ideal candidate can translate business and data requirements into technical integration blueprints and help build reliable, reusable data flows across systems.

Key Responsibilities

• Design and implement scalable data integration patterns connecting PIM, ERP, and other enterprise systems.
• Develop integration flows using REST APIs, batch processing, event-driven architecture, and data transformation techniques.
• Lead data mapping discussions and define schemas, data contracts, transformation rules, and interface specifications.
• Create developer-ready integration blueprints covering data flows, mappings, dependencies, and error-handling mechanisms.
• Build reusable, stateless integration patterns that support new data sources and downstream consumers with minimal redesign.
• Support product data synchronization, data validation, reconciliation, and troubleshooting across integrated platforms.
• Collaborate with business stakeholders, PIM teams, developers, and external partners to translate requirements into implementation-ready solutions.
• Explore AI/LLM-based approaches to improve data mapping, transformation, validation, and integration documentation.

Required Skills

• Strong experience in Data Engineering, Data Integration, or Integration/Solution Architecture .
• Hands-on knowledge of APIs, data mapping, transformation, schemas, and enterprise integration patterns.
• Experience integrating multiple enterprise systems and downstream applications.
• Ability to design technical integration flows and communicate implementation requirements clearly.