Data Architect (Retail)

Design and develop enterprise data models using Erwin for both OLTP and OLAP environments, including support for JSON and mixed data types. Create and optimize modernized web application data models focused on scalability, performance, and efficient application processing. Reverse engineer existing data models and transform them into future-state architectures aligned with business and technical requirements. Lead data modeling efforts for modernization and re-architecture initiatives across enterprise applications. Define and implement data governance and data management best practices. Evaluate and recommend appropriate database technologies on Google Cloud Platform for structured and unstructured datasets. Work across multiple database technologies including DB2, Cloud SQL, AlloyDB, BigQuery, and related platforms. Collaborate with cross-functional teams to understand retail business processes, module interdependencies, and enterprise data elements. Support Domain Driven Design (DDD) principles and architectural best practices in solution design. Guide and mentor junior data modelers and architects within an onsite-offshore delivery model. Effectively manage multiple priorities in a fast-paced and evolving environment.

Must Have Skills - Retail Data Architect Skill 1 - 8 + Years of exp in Data Architecture Skill 2 - 3 + Years of Exp in Data Modeling Skill 3- 4+ Years of exp in Erwin

Skills-

We are looking for an experienced Retail Data Architect with strong expertise in modern data architecture, retail domain knowledge, and cloud-native database technologies. The ideal candidate will play a key role in rearchitecting and modernizing enterprise business applications and data models for scalable, high-performance platforms on Google Cloud Platform., Strong hands-on experience with Erwin Data Modeling tools. Expertise in designing OLTP and OLAP data models, including JSON-based and complex data structures. Experience building high-performance data models for modern web applications. Strong understanding of data governance, metadata management, and data management principles. Experience with Google Cloud Platform database selection strategies and cloud-native architecture. Hands-on experience with technologies such as DB2, Cloud SQL, AlloyDB, BigQuery, and other modern database platforms. Strong retail domain experience with understanding of retail workflows, business processes, and data dependencies. Proven experience in rearchitecting legacy application data models for modern technology stacks. Ability to reverse engineer and modernize complex enterprise data models. Strong communication and leadership skills with experience working in onsite-offshore delivery models. Self-driven, adaptable, and capable of navigating ambiguity and changing priorities. Solid understanding of Domain Driven Design patterns and principles., Experience with enterprise modernization and digital transformation initiatives. Prior experience leading data architecture discussions with business and technical stakeholders. Exposure to cloud-native application architectures and distributed systems.