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Metro senior data-engineer role with common Azure/PySpark stack and broad skillset, moderately competitive.
Core data engineering skills transfer across industries, but healthcare preference creates moderate sensitivity.
Explicit 7–10 years and mandatory Azure Databricks, PySpark, and data-platform experience imply high shortlisting strictness.
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Lead planning, design, and implementation of a centralized data warehouse solution for ETL, reporting, and analytics across company applications.
Collaborate with Agile teams and domain experts to develop, test, implement, and support scalable data engineering solutions using Azure cloud technologies.
Analyze complex data to identify opportunities and address business problems within the healthcare revenue cycle domain.
7-10 years of experience in data engineering or related roles.
Proficiency in Python/Scala, PySpark, Spark SQL, and understanding of OOP and design patterns.
Experience with Azure cloud services including Azure Databricks, Azure Blob Storage, Azure Data Lake, and Delta Lake.
Work Experience Required: 7-10 years; Healthcare industry experience preferred but not mandatory.
Experienced in designing large scale data products and technical delivery within agile environments.
Expertise in building ETL pipelines and data visualization/dashboards using Azure Databricks.
Strong familiarity with distributed microservices and data science integration in a healthcare setting.