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Generalist data role, metro location, and broad Azure skillset drive high applicant competition.
Role requires Azure and specific data-platform expertise, limiting cross-industry transferability.
Extensive mandatory Azure, data platform, scripting skills and explicit years make filters highly strict.
Design, develop, and implement large-scale data engineering solutions on Microsoft Azure.
Handle cloud development and data lake responsibilities using Azure Data Factory, Azure Databricks, Azure EventHub, and related Azure services.
Develop and administer data products with scripting and data platform tools such as Python, Spark, Teradata, Cassandra, and SQL Server.
6 to 18 years of overall experience with at least 4 years in software solution development using agile, DevOps, and product models.
Minimum 4 years of data analytics experience using SQL.
Minimum 4 years of cloud development and data lake experience specifically on Microsoft Azure technologies including Azure EventHub, Data Factory, Functions, Databricks, Power Apps, Blob Storage, ADLS, and Azure DevOps.
Proficiency in scripting (Python, Spark, Unix) and experience with data platforms (Teradata, Cassandra, MongoDB, SQL Server, Snowflake) and CI/CD tools (GitHub, Azure DevOps, Terraform).
Senior-level professional experienced in full lifecycle cloud data engineering on Microsoft Azure environments.
Experienced in working with large-scale enterprise data platforms combining development, administration, and support.
Capable of leveraging a wide range of modern cloud and scripting technologies to deliver robust data engineering solutions.