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Mid-level popular data role with metro context and moderate brand increases applicant competition.
Core data engineering skills are transferable but Microsoft Fabric specificity limits cross-industry fit somewhat.
Explicit 3–4 years plus mandatory Microsoft Fabric and PySpark skills create stringent shortlisting filters.
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Design, develop, and maintain scalable data pipelines and ETL/ELT processes using Microsoft Fabric and PySpark.
Manage data transformation workflows involving Lakehouse, Data Warehouse, and Data Factory components within Microsoft Fabric.
Ensure data quality, consistency, and optimize pipeline performance while supporting data modeling and analytics reporting needs.
3–4 years of experience in Data Engineering or related roles.
Hands-on experience with Microsoft Fabric (Data Factory, Lakehouse, Data Warehouse, Notebooks).
Strong proficiency in PySpark and understanding of Databricks and Spark ecosystem.
Bachelor's degree in Computer Science, IT, Engineering, or related field.
Experienced working with cloud-based modern data architectures, especially Microsoft Fabric and Azure Data Services.
Technical focus on building and optimizing complex data pipelines with strong problem-solving skills.
Comfortable collaborating with business stakeholders and data teams to deliver analytics solutions.