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Remote senior Data Engineer with popular title and metro reach, attracting high applicant competition.
Strong enterprise data engineering focus (Databricks, Snowflake, SAP) makes cross-industry fit moderately constrained.
Mandatory 7-8 years, Databricks certification, Azure DevOps CI/CD and Snowflake make filters strict.
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Design, develop, and maintain scalable data pipelines and data architectures using Azure Databricks, Snowflake, and related technologies.
Own end-to-end CI/CD for data pipelines leveraging Databricks Asset Bundles (DAB) and Azure DevOps across development, QA, and production environments.
Implement and maintain data quality, validation, reconciliation checks, and pipeline observability to ensure data integrity and high availability.
7-8 years of hands-on data engineering experience with production data pipelines at scale.
Strong expertise with Azure services (ADLS Gen2, Azure Databricks, Azure DevOps) and Databricks technologies including PySpark, Spark SQL, Delta Lake, and Databricks Workflows.
Mandatory certification: Databricks Certified Data Engineer Associate or Professional.
Experience with Snowflake data modeling, performance tuning, loading, and optimization; proficiency in SQL and Python.
Deep experience integrating enterprise data sources including SAP into data lakes or warehouses using modern architectures like Lakehouse/medallion.
Proven operational ownership of CI/CD pipelines for data engineering projects with strong automation and orchestration skills.
Comfortable working remotely in India, able to collaborate effectively with cross-functional teams and stakeholders.