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 using partitioning, bucketing, caching, broadcast joins, Adaptive Query Execution, and Delta optimization.
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 Skills

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.

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

Aroha Technologies, Inc

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