Job Description :

We are seeking a highly skilled Data Engineer with deep expertise in PySpark and the Cloudera Data Platform (CDP) to join our data engineering team. As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines that ensure high data quality and availability across the organization.

Responsibilities :

- Data Pipeline Development : Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy.

- Data Ingestion : Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP.

- Data Transformation and Processing : Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements.

- Performance Optimization : Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes.

- Data Quality and Validation : Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline.

- Automation and Orchestration : Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem.

- Monitoring and Maintenance : Monitor pipeline performance, troubleshoot issues.