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Generalist Azure data engineer role in a metro with broad skill requirements attracts many qualified applicants.
Data engineering skills are generally transferable, though Azure/Databricks specialization raises domain dependency.
Explicit 6–18 years plus mandatory Azure, Databricks, SQL, Python and CI/CD requirements.
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Design, develop, and implement large-scale data engineering solutions using Microsoft Azure cloud technologies.
Leverage 4+ years of experience in cloud development, data lakes, and data analytics using SQL to build and support data pipelines.
Work with a combination of development, administration, and support activities across various tools including Azure Data Factory, Databricks, EventHub, Power Apps, and scripting languages like Python and Spark.
6 to 18 years of total professional experience.
4+ years of experience in software solution development using agile and DevOps methodologies.
4+ years of data analytics experience using SQL and cloud development experience primarily on Microsoft Azure services such as Azure Data Factory, Azure Databricks, Azure Blob Storage, and Azure Data Lake.
Experience with scripting languages (Python, Spark, Unix) and familiarity with data platforms like Teradata, Cassandra, MongoDB, and Snowflake.
Experienced in end-to-end data engineering projects using Microsoft Azure cloud platform with hands-on expertise in Azure native services.
Comfortable working in agile, DevOps-driven product development environments combining development, administration, and operational support roles.
Capable of implementing CI/CD pipelines using tools like GitHub, Azure DevOps, and Terraform for data engineering workflows.