Azure Data lead

Azure Senior Data Lead

Leads modernization of Python applications into scalable PySpark solutions on Azure Databricks

Role Purpose

Lead the modernization and migration of existing Python object-oriented applications into scalable PySpark and Spark SQL data-processing solutions on Azure Databricks - bringing a strong blend of software engineering, data engineering, cloud architecture, and performance optimization.

Key Responsibilities

• Analyze existing Python OOP applications and redesign single-node processing logic for distributed Spark execution.
• Design, develop, and deploy enterprise-scale data pipelines on Azure Databricks; build reusable PySpark frameworks and utility modules.
• Implement Delta Lake solutions using the Bronze Silver Gold architecture.
• Build robust ETL/ELT pipelines with Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
• Implement data quality, reconciliation, validation, and monitoring frameworks.
• Optimize Spark jobs (partitioning, bucketing, caching, broadcast joins, Adaptive Query Execution, Delta optimization) and benchmark converted applications against original Python implementations.

Core Skills

• Python (expert)
• OOP
• advanced Python design patterns
• PySpark
• Spark SQL
• SQL
• Azure Databricks
• Azure Data Factory
• ADLS Gen2
• Apache Spark
• Delta Lake
• Data Lakehouse architecture
• distributed computing

Must-have (per requisition)

• Python
• Azure Databricks
• Azure Data Factory (ADF)
• MS SQL
• Oracle PL/SQL

Good to have

• PySpark
• certifications in Azure Data Factory, Azure Databricks, SQL, Oracle, or Python

Experience & Expected Outcome

Senior data engineering leader with proven delivery of large-scale Databricks modernization programs.

Expected outcome: existing Python applications converted into scalable, cost-efficient, enterprise-grade data solutions on Azure Databricks with proven performance parity.