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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Data Factory, Databricks, and Azure data storage services.
Optimize and manage large-scale distributed data processing jobs in Azure Databricks using PySpark and SparkSQL focusing on performance and cost efficiency.
Implement data modeling and storage solutions across HPCC and Azure platforms ensuring high-quality, governed, analytics-ready datasets.
Minimum Requirements
4-5 years of relevant experience as an Azure Data Engineer or similar role.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
Hands-on proficiency with Azure Databricks, PySpark, SparkSQL, Azure Data Factory, ADLS Gen2, and SQL.
Good knowledge of US Insurance terminology mandatory.
Ideal Candidate Profile
Experienced working across multiple domains including US Healthcare and Insurance data environments.
Strong expertise in scalable data pipeline development and distributed processing on Azure platforms with performance tuning capabilities.
Familiarity with software development lifecycle, Agile methodologies, and data governance/security best practices in cloud environments.