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Metro location, popular Data Engineer title, and broad Azure/Databricks/Snowflake skillset increase competition.
Core data engineering skills are transferable, but Azure Databricks and Snowflake specificity raises sensitivity.
Explicit 10+ years requirement plus specific Azure/Databricks/Snowflake tech mandates create strict filters.
Design, develop, and optimize scalable data pipelines, data warehouses, and analytics solutions using Azure Databricks, Azure Data Factory, Snowflake, Python, PySpark, and SQL.
Implement data quality and governance frameworks to ensure reliable data for business intelligence and reporting.
Collaborate with business stakeholders and manage Agile delivery processes to support analytics, KPI reporting, and data migration initiatives.
10+ years of experience in data engineering focused on Azure Databricks, Azure Data Factory, Snowflake, Python, PySpark, and SQL.
Strong expertise in ETL development, data modeling, and data warehousing.
Experience with data governance and Agile methodologies.
Work Experience Required: 10+ years
Experienced in delivering complex, scalable data solutions in Azure cloud environments, especially Databricks and Data Factory.
Ability to engage effectively with business stakeholders for requirements gathering and continuous collaboration.
Proficient in managing Agile project delivery and implementing data governance frameworks.