CLOUD AMAZE - DW Architect (Practice)

Job Title: Data Lake / Lakehouse Data Modeler — Azure (Banking)

Location: Jersey City, NJ

Role Summary

Seeking a Data Lake/Lakehouse Data Modeler with deep hands-on experience building governed, secure, and high-performance data models on Azure for banking use cases. The role will design logical and physical schemas across landing, curated, and serving layers to support regulatory reporting, risk & finance analytics, fraud detection, AML, customer 360, and ML use cases while ensuring compliance, lineage and operational SLAs.

Key Responsibilities:

• Design logical and physical models across raw, curated, and consumption layers optimized for lakehouse patterns.
• Define canonical models and source-to-target mappings for transactions, accounts, customers, loans, payments, and exposures.
• Define retention, archival, encryption (CMK), and access controls using Azure Key Vault and Azure AD.
• Work with data engineers and platform teams to implement models in Databricks and Synapse with CI/CD and tests.
• Perform data profiling, validation, and iterative tuning to meet performance and SLAs for BI and ML consumers. Required Qualifications:
• Proven experience modeling lakehouse or data lake solutions for banking or financial services.
• Deep domain knowledge of payments, ledgers, credit lifecycle, risk metrics, and regulatory reporting needs.
• Hands-on experience with ADLS Gen2, Azure Databricks (Delta Lake), and Azure Synapse Analytics.
• Practical experience with CDC, streaming, low-latency analytics, and schema evolution strategies.
• Familiarity with Purview, Azure AD, Key Vault, network isolation, and regulatory compliance controls.
• Delta Lake, Parquet/ORC, schema evolution, partitioning and Z-order/clustering strategies.
• Spark SQL, Databricks notebooks, dbt or similar modeling frameworks, and strong SQL proficiency.
• Ingestion and orchestration with ADF/Synapse Pipelines, Event Hubs, Stream Analytics, and Airflow/Jobs.
• BI and analytics integration using Power BI, Synapse SQL, and Databricks SQL for served models.
• Strong stakeholder engagement across compliance, risk, finance, engineering, and data science teams.
• Clear documentation, model governance, and ability to present designs for audits and architecture reviews.
• 10 + years of experience in data modeling or data engineering with banking experience preferred;
• 5 plus years of experience with different modeling tools like Erwin/ Embarcadero or ER Studio
• Azure or Databricks certifications valued.
• Deliverables : Model artifacts and data dictionaries, source-to-target mappings, lineage for audits, and measurable performance and quality improvements.

Technical Skills:

Experience & Education: