Lead Big Data Innovator
2 days ago
Job Overview:
We are seeking a highly skilled Data Engineer to join our organization. In this role, you will be instrumental in designing and developing efficient ETL processes using Databricks PySpark.
Key Responsibilities:
- ETL Development:
- Design and develop ETL processes using Databricks PySpark to extract, transform, and load data from various sources into data lake and data warehouse.
- Optimize ETL workflows for performance and scalability, leveraging Databricks PySpark and Spark SQL to efficiently process large data volumes.
- Implement robust error handling and monitoring mechanisms to proactively detect and resolve issues within ETL processes.
- Ensure data is appropriately cleansed, enriched, and optimized at each stage to support robust analytics and reporting.
- Data Pipeline Management:
- Create advanced data pipelines using Databricks workflows.
- Develop and maintain data pipelines using Databricks PySpark, ensuring data quality, integrity, and reliability throughout the ETL lifecycle.
- Data Analysis and Query Optimization:
- 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 and coordination activities to ensure timely delivery of ETL solutions.
- Stay updated on the latest developments in Databricks PySpark, Spark SQL, and related technologies, recommending and implementing best practices and optimizations.
- Document ETL processes, data lineage, and metadata to facilitate knowledge sharing and ensure compliance with data governance standards.
Required Skills:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Minimum of 3 years of experience as an ETL developer, with a strong focus on Databricks PySpark development.
- Proficiency in Python programming, with extensive experience in developing and debugging Databricks PySpark applications.
- In-depth understanding of Spark architecture and internals, with hands-on experience in Spark RDDs, DataFrames, and Spark SQL.
Preferred Qualifications:
- Experience with cloud platforms with a preference for AWS.
- Relevant certifications in Databricks PySpark, Spark SQL, or related technologies.
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