Job Description
JD — Enterprise Data Architect (Databricks)
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nExperience Total : 10+ years in data / analytics engineering
nData architecture : 8+ years
nDatabricks (design and delivery) : 3+ years
nSalesforce Data Cloud exposure : 1+ year
nBudget : 1.6 LPM
nDuration : 6 Months
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nMust-have skills
n* 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.
n* 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.
n* Identity-resolution design : deterministic match-key vetting, rule precedence, survivorship, unmatched-residual measurement, and how a CDP consumes that design.
n* Source-to-target and pipeline strategy : has produced source registers,



latency maps and extraction-pattern decisions for 10+ heterogeneous SaaS, CRM and web-analytics sources.
n* 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.
n* Specification authorship : writes design documents other engineers build from unaided and is comfortable being the named signatory for build ready.
n* Stakeholder facilitation at architect level : runs decision sessions with enterprise architects and business owners and closes open decisions with a defensible rationale.
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nGood to have
n* Marketing-data or CDP programmes: Pardot / Account Engagement, Sitecore, Seismic, ZoomInfo, GA4 / BigQuery, Cvent, SalesLoft.
n* Semantic-layer and metric-view design (Databricks metric views, Tableau / Tableau Next).
n* Data-gover

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