Databricks Data Engineer

CRG is seeking a Databricks Data Engineer to support the Retail Spine initiative. The role focuses on building and optimizing data pipelines and scalable Azure data solutions, including CDC, streaming, data quality, and data modeling workflows.

Responsibilities:

• Design, build, and optimize end-to-end ETL/ELT pipelines using Databricks and Apache Spark (PySpark)
• Develop and maintain scalable data solutions on Microsoft Azure, leveraging Databricks, Delta Lake, and Kafka streaming
• Build robust pipelines with Change Data Capture (CDC) to support incremental data processing and real-time/near real-time data needs
• Work across both new pipeline development and enhancement of existing pipelines, quickly understanding current codebases to deliver improvements
• Integrate and process data from diverse sources including: Flat files, XML, JSON, SQL Server and JDBC systems, Kafka topics, APIs, MQ, Unity Catalog volumes and other enterprise platforms
• Implement data quality frameworks, including writing technical data quality rules and quarantining error records
• Apply canonical data modeling techniques, including SCD Type 1 and Type 2 implementations
• Ensure high levels of data reliability, performance, scalability, and monitoring across all workflows
• Automate workflows using Databricks Workflows and CI/CD pipelines (GitHub), focusing on reuse, efficiency, and standardization
• Collaborate with developers, architects, and product owners, and engage with stakeholders, source teams, and downstream consumers as needed
• Participate actively in Agile/Scrum ceremonies and deliver high-quality solutions within defined timelines

Requirements:

• Extensive hands-on experience with Databricks, with ability to contribute from day one
• Proven experience building end-to-end data engineering pipelines with CDC capabilities
• Strong proficiency in PySpark and SQL (required)
• Experience working in Microsoft Azure cloud environments
• Delta Lake
• Distributed data processing frameworks
• Streaming technologies (Kafka)
• Data modeling (SCD Type 1 & Type 2)
• Experience integrating data from multiple structured and unstructured data sources
• Familiarity with GitHub and CI/CD pipelines for version control and deployment
• Strong understanding of data architecture, performance optimization, and pipeline scalability
• Python experience is a plus