We are seeking a Senior Data Engineer with strong expertise in PySpark, Snowflake, and Microsoft Azure to build and optimize scalable, cloud-based data solutions.
Responsibilities
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Design, develop, and optimize data pipelines using PySpark
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Build and manage data ingestion and transformation processes in Azure
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Develop and maintain data models and transformations in Snowflake
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Optimize Snowflake performance (clustering, warehouses, cost optimization)
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Work with large-scale structured and semi-structured datasets
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Implement data quality, validation, and monitoring frameworks
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Collaborate with data architects, analysts, and stakeholders
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Ensure security, governance, and compliance in Azure data solutions
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Troubleshoot and resolve pipeline failures and performance issues
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Mentor junior engineers and contribute to best engineering practices
Requirements:
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5+ years of experience in Data Engineering
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Strong hands-on experience with PySpark / Apache Spark
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Advanced proficiency in Python
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Strong experience with Snowflake (SQL, performance tuning, cost control)
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Hands-on experience with Azure services, including:
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Azure Data Factory (ADF)
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Azure Data Lake Storage (ADLS Gen2)
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Azure Synapse Analytics
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Strong SQL skills and data modeling knowledge
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Experience with ETL/ELT architectures