Azure Data lead

Job Title: Azure Data lead

Location: NYC ,NY(Hybrid)

Job Type: Contract Position

Job Description

Azure Data lead - Python, Pyspark, Databricks, ADF, Data Lake,

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, and advanced Python design patterns

• PySpark, Spark SQL, and 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.