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Data Engineer with SQL and Databricks Exp.-In Person InterviewMagicforceUnited States
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Data Engineer with SQL and Databricks Exp.-In Person Interview

Magicforce
  • US
    United States
  • US
    United States

À propos

Overview:

ETL / ELT Concepts:
Strong understanding of pipeline patterns, incremental loads, data validation, and troubleshooting.

SQL:
Advanced querying (CTEs, views, joins, complex query logic) and performance tuning for transformations and validation. Python: Production-quality development (modular code, testing, logging, integration with APIs/files, CICD, Unit Test/Integration test automation, Code Coverage).

PySpark:
Distributed transformations and performance optimization (joins, partitions, debugging), CICD, Unit Test/Integration test automation, Code Coverage.

Azure Data Factory (ADF):
Build/operate ADF pipelines, parameterization, triggers, monitoring, retry/error handling; integrate with Databricks/ADLS.

Databricks:
Develop and operationalize notebooks/jobs/workflows; Delta Lake patterns; basic cluster/job configuration.

Azure Fundamentals + Pulumi:
Hands-on with ADLS Gen2, Azure Portal, Storage Explorer, Resource Groups, Azure SQL, and familiarity integrating with Azure OpenAI. Able to use/maintain Pulumi scripts for provisioning and managing Azure resources across environments
Nice to have skills: -
• Ability to support/translate validation rules with SQL scripts and create data quality reports. TypeScript: Useful for pulumi pipeline to create Azure components.
• Java: Useful for integration with existing services/components.
• .NET: Useful for integration with existing services/components. Angular / Spring Boot: Minor troubleshooting or coordination with app teams.
Skills:
Azure (Bigdata Azure) ADF, DataBricks, Python, Pyspark
  • United States

Compétences linguistiques

  • English
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