Senior Snowflake Data Engineer

Skillset

• Experience:
  
  5 to 10 years
• Must have:
  Snowflake (certification is mandatory), ADF, Python, SQL, ETL & DWH concepts, Dev Ops.
• Good to have:
  Pyspark.
• Mandatory certification:
  Snow Pro® Advanced:
  Data Engineer certification

• Design, develop, and maintain scalable Python-based data pipelines using Azure Data Factory, Databricks (PySpark), and Snowflake.
• "Design, Develop and Maintain scalable data pipelines using Azure Data Factory, Databricks and Snowflake. Experience in Python programming and SQL is a must with exposure to data warehousing concepts."
• Develop and orchestrate data workflows and cloud artifacts including batch/streaming pipelines, integrating with Azure services (Event Hubs, Function Apps, EMS).
• Implement, test, document, and manage code with CI/CD practices via Azure Dev Ops, including pull requests and environment deployments.
• Troubleshoot and debug cloud-based data solutions, ensuring performance, security, and reliability across pipeline executions.
• Collaborate cross-functionally with data architects, analysts, data engineers, and business stakeholders to ensure successful and timely project delivery.