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Popular data engineering role across multiple metros with moderate employer brand and broad applicant pool.
Core data engineering skills transfer across industries, but Azure-specific toolset increases domain preference.
Multiple explicit years and extensive mandatory Azure and data platform skill requirements create strict shortlisting filters.
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Design, develop, and implement large-scale data engineering solutions using Azure cloud technologies and big data tools.
Develop and maintain data analytics workflows primarily using SQL, PySpark, and Python across Azure Data Factory, Azure Databricks, and related services.
Operate within an Agile DevOps environment managing CI/CD with tools like GitHub, Azure DevOps, and Terraform.
Total experience of 10+ years with at least 4+ years in software solution development using Agile and DevOps methodologies.
4+ years of experience in data analytics using SQL and cloud development focused on Microsoft Azure data lake and related services.
Proficiency in Azure technologies including Azure Data Factory, Azure Databricks, Azure Functions, Azure Blob Storage, Azure Data Lake, Azure Power Apps, and Azure Data Explorer.
Experience with Python, Spark, PySpark, Unix scripting, and knowledge of data platforms such as Teradata, Cassandra, MongoDB, and Snowflake.
Strong experience in integrating development, administration, and support activities across Azure cloud data services and big data platforms.
Experience working in Agile, DevOps driven environments with hands-on CI/CD using GitHub, Azure DevOps, and Terraform is crucial.
Demonstrated ability to build and maintain complex data pipelines and analytics workflows leveraging Microsoft Azure ecosystem and relevant scripting languages.