Data Architect || Golbal Consulting Firm || Bangalore

· Enterprise product-company background preferred - versioned migrations, release discipline, and backup and recovery you were personally accountable for. A services background works if you owned a platform rather than delivered someone else's specification.

· You have taken a data platform from zero - started with an empty schema and made the calls everything afterwards had to live with.

· You have designed a data model more than one team had to live inside, and can say what you got wrong and what it cost to fix.

· Opinions about identity - what makes two records the same real thing - and a resolver you built that had to be right rather than merely plausible.

· Modelling depth. Dimensional and graph modelling, master data management, entity resolution at scale, and ontology and taxonomy modelling as a discipline in its own right - not document retrieval, which is a different craft.

· Domain advantage. Product, parts, supplier or spend data models - PLM, procurement, catalog or master-data products. If you have argued about why one supplier exists under four names, we do not have to explain this job to you.

· Databases. Deep relational and graph experience, including row-level security, recursive queries and vector search. Production experience of at least one warehouse or lakehouse platform. You know why a constraint in the database beats a rule in the pipeline.

· Multi-tenant data where a leak is a serious event, and a fail-closed default.

· Cloud and infrastructure as code - Kubernetes, managed data services and Terraform in production. Azure preferred; AWS acceptable.