Azure Databricks SME

• Design, develop, and maintain scalable ETL/ELT pipelines using Azure Databricks and Py Spark
• Build and optimize data ingestion frameworks for structured, semi-structured, and unstructured data sources
• Develop and maintain Delta Lake architectures utilizing Bronze, Silver, and Gold data layers
• Create and optimize Databricks notebooks, workflows, and jobs for batch and real-time processing
• Integrate data from APIs, SQL databases, flat files, Kafka streams, cloud storage, and enterprise applications
• Design and implement data quality, validation, monitoring, and error-handling frameworks
• Leverage Azure Data Factory (ADF) for orchestration and pipeline automation

We are seeking a Senior Data Engineer with deep expertise in Azure Databricks to design, develop, and optimize scalable cloud-based data solutions. This role will focus on building enterprise-grade data pipelines, implementing modern data Lakehouse architectures, and enabling advanced analytics through Azure-native technologies. The ideal candidate has extensive experience with Databricks, PySpark, Delta Lake, Azure Data Factory, and cloud-based data engineering best practices

$65/hr to $75/hr

Exact compensation may vary based on several factors, including skills, experience, and education.

Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.