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Metro location and popular Data Engineer title increase competition, but niche Snowflake/DBT skills moderate it.
Cloud data engineering skills transfer across industries, but Snowflake/ADF specialization raises moderate domain bias.
Explicit 8+ years and mandatory Azure, ADF, Snowflake, DBT requirements make filters strict.
Design, develop, and optimize ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
Build and maintain data integration workflows from multiple sources into Snowflake with efficient SQL queries.
Collaborate with stakeholders and cross-functional teams to translate business requirements into cloud-native technical solutions and ensure data quality and governance.
8+ years experience in data engineering with Azure and Snowflake.
Bachelor’s or master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
Strong expertise in Azure Cloud Platform services, especially Azure Data Factory (ADF).
Proficiency in SQL and hands-on experience with Snowflake and DBT.
Experienced in managing large-scale cloud-based data environments specializing in Azure and Snowflake.
Skilled in translating complex business needs into scalable data engineering solutions using modern cloud-native tools.
Collaborative working style involving multiple stakeholders including data analysts, architects, and DevOps teams.