Enterprise Azure Data Architect

Requirements:
12+ years of overall IT experience with deep expertise in data architecture and Azure Data Platform solutions.
Strong understanding of big data processing, schema-on-read, data lakehouse architectures, and modern enterprise data warehousing.
Hands-on architectural and implementation experience with Azure Data Factory (ADF), Azure Databricks (PySpark), Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Synapse Analytics, and Microsoft Fabric is a must.
Proven ability to design scalable, secure, resilient, and cost-efficient data architectures on Azure.
Strong proficiency in Python (PySpark mandatory) and SQL.
Familiarity with Power BI DAX is a plus.
Experience designing enterprise-grade ETL/ELT frameworks, metadata-driven pipelines, reusable ingestion patterns, and orchestration strategies.
Solid expertise in data modelling (Kimball, Inmon, Data Vault, SCD Type 2) for warehouse and lakehouse implementations.
Strong knowledge of data governance, data quality frameworks, lineage, cataloguing, and security models including RBAC, data masking, and row/column-level security.
Experience with cost management, capacity planning, performance tuning, and optimisation of Azure data workloads (compute, storage, and query performance).
Understanding of Azure infrastructure concepts including networking (VNet, Private Endpoints), identity (AAD, Managed Identity), resource organisation, and subscription management.
Experience with CI/CD, DevOps practices, Infrastructure as Code (ARM/Bicep/Terraform), and automated deployments for data platforms.
Experience designing semantic layers and reporting models for Power BI and Tableau.
Good to Have: Hands-on or architectural exposure to Microsoft Fabric, including Lakehouse, Warehouse, Data Engineering, Data Pipelines, capacity management, and Power BI integration.

Experience
12-15 yrs