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Generalist Data Engineer title, mid-level experience range and broad stack imply moderate competition.
Healthcare finance domain expertise requirement makes cross-industry transition difficult.
Many mandatory AWS, PySpark, Iceberg, Glue, and healthcare-domain requirements raise screening strictness.
Design and build scalable data architectures and ETL/ELT pipelines using Python, PySpark, and AWS Glue.
Manage and optimize AWS data services environment including S3, Redshift, Lambda, EMR, with a focus on Apache Iceberg format for data lake.
Provide technical leadership on complex data engineering projects and collaborate cross-functionally to deliver predictive and prescriptive analytics solutions.
Strong hands-on experience with Python and PySpark for data processing.
Proficient in complex SQL queries and managing large datasets.
Experience with AWS Data Lake environments, specifically using Apache Iceberg format, and AWS Glue Jobs.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in healthcare finance systems with strong understanding of associated data processes.
Skilled in designing data solutions that align with enterprise architecture standards.
Comfortable working in Agile environments with cross-functional teams to translate business requirements into data solutions.