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Metro location and common data-engineering title, but senior level and niche Snowflake/Azure skills moderate competition.
Core cloud data engineering skills (Azure, Snowflake, DBT) are moderately transferable across industries.
Mandatory 8+ years and specific Azure, ADF, Snowflake, and DBT requirements make filters highly strict.
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Design, develop, and maintain ETL/ELT data pipelines using Azure Data Factory, Snowflake, and DBT.
Write optimized SQL queries for data extraction and transformation and manage data integration from multiple sources into Snowflake.
Monitor and optimize pipeline performance while enforcing data quality, governance, and collaborating with cross-functional cloud-native teams.
8+ years of experience in data engineering roles with Azure and Snowflake.
Strong expertise with Azure Cloud Platform services, especially Azure Data Factory, Snowflake, and DBT.
Proficient in SQL for data analysis and transformation.
Bachelor’s or master’s degree in computer science, data engineering, information systems, or related field.
Experienced in cloud-native data engineering environments managing large-scale datasets.
Skilled in translating business requirements into technical solutions involving data workflows and governance.
Collaborative working style involving data analysts, architects, and DevOps teams.