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Senior Data Engineer Position

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Job Title

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Data Engineering Role

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  • Key Responsibilities
    • ETL Development:
      • Design and develop efficient data extraction, transformation, and loading processes using Databricks PySpark.
      • Optimize ETL workflows for performance and scalability to efficiently process large data volumes.
      • Implement robust error handling and monitoring mechanisms to proactively detect and resolve issues within ETL processes.
      • Design and implement data solutions following scalable architecture principles, organizing data into tiered layers.
      • Ensure data is appropriately cleansed, enriched, and optimized at each stage to support robust analytics and reporting.
    • Data Pipeline Management:
      • Hands-on experience in creating advanced data pipelines using Databricks workflows.
      • Develop and maintain data pipelines using Databricks PySpark, ensuring data quality, integrity, and reliability throughout the ETL lifecycle.
      • Collaborate with cross-functional teams to translate data requirements into efficient ETL workflows and pipelines.
    • Query Optimization and Data Analysis:
      • Write and optimize complex SQL queries for data manipulation, aggregation, and analysis within Databricks PySpark applications.
    • Project Coordination and Continuous Improvement:
      • Participate in project planning activities to ensure timely delivery of ETL solutions.
      • Stay updated on the latest developments in Databricks PySpark, Spark SQL, and related technologies, recommending best practices and optimizations.
      • Document ETL processes, data lineage, and metadata to facilitate knowledge sharing and ensure compliance with data governance standards.