Back
Popular mid-level Data Engineer with common 4+ years requirement and broad skillset, increasing competition.
Core data engineering skills are transferable across industries despite preferred insurance domain experience.
Explicit 4+ years and mandatory Azure/Microsoft Fabric, PySpark, SQL and governance tooling increase filter strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and maintain Microsoft Fabric / OneLake Lakehouse solutions across Bronze, Silver, and Gold layers using Medallion Architecture.
Build, optimize, and troubleshoot scalable data ingestion and transformation pipelines using Spark / PySpark, Python, SQL, and Fabric Data Pipelines.
Implement data quality, validation, reconciliation, security, and governance frameworks supporting analytics and Power BI consumption.
4+ years of Data Engineering experience with hands-on Azure / Microsoft Fabric skills.
Proficiency in Spark / PySpark, Python, SQL, Delta Lake, and experience with ETL/ELT, CDC, and data transformation.
Bachelor's degree in Computer Science, Engineering, Information Technology or related field.
Experience with Microsoft Fabric Lakehouse, OneLake, Warehouse, Data Pipelines, Notebooks, and knowledge of Power BI semantic models and Direct Lake.
Experienced building enterprise-scale data platforms with layered architectures (Bronze, Silver, Gold) using Microsoft Fabric technologies.
Proficient in implementing robust data quality, validation, and operational monitoring in complex data pipelines.
Candidates familiar with commercial insurance or brokerage data domain preferred but not mandatory.