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Mid-level metro Data Engineer role with broad Azure/Databricks requirements increases candidate competition.
Core data engineering and cloud skills are highly transferable across industries despite insurance preference.
Explicit 3-6 years and mandatory Azure, Databricks, PySpark, Delta-specific skills make shortlisting highly strict.
Design, develop, and maintain scalable data pipelines and workflows primarily using Azure and Databricks technologies to support enterprise reporting and analytics.
Implement data validation, monitoring, and troubleshooting mechanisms to ensure data accuracy, integrity, and high availability.
Collaborate with cross-functional teams to support insurance domain use cases, ensuring compliance with data governance and regulatory requirements.
3-6 years of experience in Data Engineering with hands-on expertise in Databricks and Azure Cloud technologies.
Bachelor’s degree in Computer Science, Information Technology, or related field.
Strong proficiency in PySpark, Python, SQL; experience with Azure Data Factory, Azure Databricks, Azure Data Lake, Delta Lake, and data modeling.
Experience with ETL/ELT pipeline development, automation, performance tuning, and familiarity with Agile methodologies (scrum, sprint planning).
Experienced in building robust data engineering solutions specifically on Azure cloud components and Databricks platform.
Strong understanding of insurance industry data requirements and governance is preferred to enhance domain-relevant data solutions.
Demonstrated ability to manage complex data workflows with focus on data quality, compliance, and cross-team collaboration under Agile delivery models.