{"id":1011311,"url":"https://alion.io/job/snap-data-architect","title":"Data Architect","company":{"id":8998,"name":"Snap","domain":"snap.com","url":"https://alion.io/company/snap","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":100,"open_postings":7,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, 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models.\nDefine and enforce enterprise data standards (naming, normalisation, domains, data types).\nMaintain data dictionaries, model documentation, and change control processes.\nMaster Reference Data Management:\nArchitect and implement Master Data Management (MDM) solutions using Informatica MDM, covering Customer, Product, Supplier, Pricing, and Party domains.\nDesign golden record, match-merge rules, survivorship logic, and source system trust frameworks.\nDefine and manage reference data models (code sets, hierarchies, value lists) using Informatica R360\nEstablish stewardship workflows, data governance alignment, and lifecycle management for master and reference data.\nEnsure consistent propagation of mastered and reference data to downstream platforms including Databricks, ERP, CRM, and OMS systems.\nData Architecture:\nDatabricks Lakehouse.\nDefine data architecture patterns for Databricks Lakehouse using Delta Lake, Unity Catalogue, and medallion (Bronze/Silver/Gold) architecture.\nTranslate enterprise transactional and MDM models into optimised analytical schemas and data marts.\nPartner with data engineering teams to implement ELT/ETL pipelines (Spark SQL / PySpark) with data validation and reconciliation.\nTransactional, Master and Reference Data systems integration.\nRequirements:\n10+ years of experience in enterprise data modelling and data architecture roles.\nStrong hands-on experience with Erwin Data Modeller in large-scale environments is preferred.\nExperience with Databricks (Delta Lake, Spark, Unity Catalogue).\nAdvanced SQL and strong understanding of normalised, dimensional, and canonical modelling approaches.\nExperience integrating major enterprise applications (ERP, CRM, OMS, MDM, AR systems).\nStrong understanding of data governance, data quality, metadata, and lineage.\nExcellent communication skills across business and technical audiences.\nCore Technology Stack:\nModelling: Erwin Data Modeller.\nAnalytics Platform: Databricks 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