Databricks Architect / Senior Architect | Azure | GenAI | PySpark | Da

Role & responsibilities

• Design scalable enterprise data platforms using Azure and Databricks.
• Architect Lakehouse solutions using Delta Lake and Unity Catalog.
• Build metadata-driven data engineering frameworks.
• Develop scalable data pipelines using PySpark and Spark SQL.
• Optimize Spark jobs for performance and cost.
• Design dimensional and normalized data models.
• Build and deploy GenAI/LLM-powered applications.
• Guide AI-assisted software engineering using Copilot, Claude Code, Gemini Code, or Codex.
• Review AI-generated code and establish engineering best practices.
• Implement CI/CD using Azure DevOps, Git, or Jenkins.
• Collaborate with business stakeholders and delivery teams.
• Mentor engineers and provide technical leadership.

Mandatory Skills

• Azure Databricks
• PySpark
• Spark SQL
• Azure Data Factory
• Azure Data Lake Storage (ADLS Gen2)
• Delta Lake
• Unity Catalog
• Microsoft Fabric
• Azure SQL
• Python
• SQL
• Data Lakehouse Architecture
• Data Modeling
• GenAI / LLM
• Azure Cloud
• Git
• Azure DevOps / Jenkins

Good to Have

• Delta Live Tables
• Databricks Workflows
• SQL Warehouse
• Mosaic AI
• AI/BI Genie
• Azure Purview
• Event Hub
• Cosmos DB
• Azure Data Explorer
• Neo4j
• Elasticsearch
• Vector Databases
• MCP
• Claude Code
• GitHub Copilot
• Gemini Code
• Codex
• Azure Infrastructure & Security

Education

Bachelor’s Degree (B.E./B.Tech) in Computer Science, IT, or related discipline.

Preferred Candidate Profile

• 8+ years of Data Engineering experience.
• 4+ years of Azure Databricks experience.
• Strong expertise in PySpark and Spark optimization.
• Experience designing enterprise-scale Lakehouse architectures.
• Hands-on experience with Azure cloud services.
• Exposure to GenAI and Agentic AI development.
• Excellent communication and stakeholder management skills.
• Architecture and solution design experience is preferred.

Preferred candidate profile