We are seeking a highly experienced and visionary Azure Databricks Architect with 12 to 14 years of total IT experience to lead the strategy, design, and implementation of enterprise-grade cloud data platforms. In this role, you will be responsible for defining modern Lakehouse architectures using Azure Databricks, architecting scalable data integration pipelines, driving data governance, and guiding organizations through complex data modernization and cloud transformation journeys.

Key Responsibilities

Architectural Design & Strategy

- Lakehouse Blueprinting: Design and deploy enterprise-scale Delta Lakehouse solutions leveraging the Medallion Architecture (Bronze, Silver, Gold layer design pattern) on Azure Databricks.
- Cloud Data Integration: Define end-to-end data ingestion, processing, and orchestration frameworks integrating Azure Databricks with Azure Data Factory (ADF), Azure Event Hubs/Kafka, Azure Synapse Analytics, and Azure Data Lake Storage Gen2 (ADLS Gen2).
- Legacy Modernization: Lead technical strategy for migrating legacy on-premises or cloud environments (e.g., Hadoop, Teradata, Netezza, SQL Server) to native Azure Databricks platform architectures.
- GenAI & Analytics Enablement: Architect data environments that support Machine Learning workflows, MLOps, MLflow, and Generative AI applications integrated with Databricks Vector Search and Feature Store.





Governance, Security & Compliance Required Qualifications & Experience

- Total Experience: 12 to 14 years in IT and Data Engineering/Architecture.
- Architect Experience: Minimum 45 years in a lead Cloud Data Architect role, with dedicated, hands-on focus on Azure Databricks and Delta Lake ecosystems.

- Core Technical Stack:
- Databricks Ecosystem: Databricks Lakehouse Platform, Unity Catalog, Delta Lake, Structured Streaming, Databricks SQL, MLflow, Auto Loader.
- Azure Cloud Services: ADLS Gen2, Azure Data Factory (ADF), Azure Synapse Analytics, Azure Event Hubs, Azure Key Vault, Azure Functions, Azure Cosmos DB.
- Languages: Python (PySpark), SQL, Scala.
- DevOps & IaC: Terraform, Azure DevOps, Git, ARM templates, Databricks Asset Bundles (DABs).
- Data Modeling: Dimensional Modeling (Star/Snowflake), Data Vault 2.0, Relational vs. NoSQL schema design patterns.
- Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Software Engineering, or a related quantitative field.

Preferred Certifications

- Databricks Certified Data Engineer Skilled or Databricks Certified Solution Architect
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
- Microsoft Certified: Azure Data Engineer Associate (DP-203)

📌 Azure Data Architect (Bengaluru)
🏢 Tenarai Technologies
📍 Bengaluru