JD — Enterprise Data Architect (Databricks) Experience Total : 10+ years in data / analytics engineering Data architecture : 8+ years Databricks (design and delivery) : 3+ years Salesforce Data Cloud exposure : 1+ year Budget : 1.6 LPM Duration : 6 Months Must-have skills * Databricks architecture, hands-on : Delta Lake (MERGE, change data feed, liquid clustering, time travel), Unity Catalog (lineage, row filters / column masks), Delta Live Tables / Lakeflow, Workflows; has designed a medallion Lakehouse that is in production. * Kimball dimensional modelling at expert level : star schemas, conformed dimensions, SCD Type 2, bridge tables, accumulating-snapshot facts, degenerate dimensions, surrogate-key strategy, declared grain. Has personally finalized a 30+ table model. * Identity-resolution design : deterministic match-key vetting, rule precedence, survivorship, unmatched-residual measurement, and how a CDP consumes that design. * Source-to-target and pipeline strategy :



has produced source registers, latency maps and extraction-pattern decisions for 10+ heterogeneous Saa S, CRM and web-analytics sources. * Working knowledge of Salesforce Data Cloud / Data 360 : Data Lake Objects, Data Model Objects, harmonization, Unified Individual, calculated insights, segments, consent — enough to design the hand-off and the batch-versus-zero-copy trade-off. * Specification authorship : writes design documents other engineers build from unaided and is comfortable being the named signatory for build ready. * Stakeholder facilitation at architect level : runs decision sessions with enterprise architects and business owners and closes open decisions with a defensible rationale. Positive to have * Marketing-data or CDP programmes: Pardot /

📌 Enterprise Data Architect (Databricks) (Uttar Pradesh)
🏢 Asian Hires Placement Consultant
📍 Uttar Pradesh