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Mid-level Data Engineer, common skillset, and metro location create high applicant competition.
Data engineering skills are broadly transferable across industries despite Azure/SSIS specifics.
Explicit 2–5 years requirement plus mandatory SSIS, ADF, SQL and Databricks skills increases filter strictness.
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Develop, test, and deploy ETL processes using SSIS and Azure Data Factory for data integration and enhancement of on-premises systems.
Identify and resolve client data issues through collaboration with internal teams and clients, ensuring data quality and process reliability.
Ensure compliance with security, privacy, and regulatory requirements while suggesting and implementing system performance improvements.
2-5 years of experience in SQL Server development.
Proficiency in SSIS, Azure Data Factory, and ETL processes.
Bachelor’s degree in computer science or related field, or equivalent experience.
Experience with Azure cloud technologies and Data Bricks; knowledge of Python is noted but not explicitly mandatory.
Experienced in SQL Server and ETL pipeline development with hands-on skills in SSIS and Azure Data Factory.
Capable of independently troubleshooting complex data issues and collaborating to resolve client-related problems.
Comfortable operating within regulated environments requiring attention to security, privacy, and compliance standards.