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Mid-level, metro-based Azure Data Engineer role with broad in-demand skills attracts strong applicant density.
Azure Databricks and cloud-specific tooling moderately reduce cross-industry transferability.
Explicit 3–6 years plus mandatory Azure Databricks, ADF, Synapse, Python/Spark requirements enforce strict shortlisting.
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Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Azure Data Factory, Databricks, and Synapse Analytics.
Integrate AI and Machine Learning services like Azure AI, OpenAI, Machine Learning, and Cognitive Services into enterprise applications.
Implement data governance, optimize platform performance, support CI/CD with Azure DevOps, and collaborate with cross-functional teams to deliver AI-driven data solutions.
3 to 6 years of experience in Data Engineering and Azure Cloud technologies.
Bachelor's or Master's degree in Computer Science, IT, Data Science, or related field.
Strong experience with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Data Lake, Python, SQL, and Spark.
Knowledge of AI/ML integration, Generative AI on Azure, cloud architecture, security, and performance optimization.
Experienced with building and optimizing large-scale data platforms and pipelines in Azure cloud environments.
Familiarity with integrating AI/ML services including Generative AI and Azure OpenAI into enterprise data applications.
Skilled in Agile development, CI/CD pipelines, Infrastructure as Code, and collaborative cross-disciplinary teamwork.