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Remote, mid-level Data Engineer with popular Azure skills yields high applicant density despite smaller employer.
Skills transferable across sectors but Azure Databricks, Delta Lake, and Azure-specific tooling increase domain specificity moderately.
Mandatory 4–7 years plus specific Azure Databricks, PySpark, ADF, Delta Lake, and CI/CD requirements make screening strict.
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Design, develop, and maintain scalable data pipelines and Lakehouse architectures using Azure Databricks, Azure Data Factory, and related Azure data services.
Develop Delta Lake-based data models and implement data quality checks, monitoring, and error-handling frameworks.
Create and maintain CI/CD pipelines with Azure DevOps and collaborate with stakeholders to support reporting and AI initiatives.
4-7 years of relevant work experience in data engineering.
Proficiency in Azure Databricks, PySpark, Spark SQL, Azure Data Factory, ADLS Gen2, and Delta Lake.
Bachelor's degree in Engineering (B.E./B.Tech), MCA, or equivalent.
Experience with Azure DevOps, CI/CD pipelines, and SQL Server scripting required.
Experienced in building end-to-end data pipelines and Lakehouse architectures on Azure platforms.
Skilled in integrating data from diverse sources including ERP, CRM, APIs, and IoT.
Capable of troubleshooting production issues, optimizing pipeline performance, and collaborating with cross-functional teams including analytics and data science.