Pyspark Data Engineer

Clover Infotech; Dubai; On-site; AED 240,000 - 360,000; Full time

Job summary

Clover Infotech in the United Arab Emirates seeks a Data Engineer with strong PySpark and Cloudera Data Platform (CDP) expertise to design and maintain scalable data pipelines. You will ensure data quality and availability across the organization and work with a team of data engineers to drive business insights.

The role emphasizes ingestion, transformation, and optimization, leveraging big data ecosystems and cloud-native tools to deliver robust data solutions for analytics and reporting.

Qualifications

• Proven experience building scalable ETL pipelines with PySpark on CDP.
• Strong data ingestion, transformation, and validation capabilities.
• Experience optimizing PySpark and CDP components for performance.
• Familiarity with data quality checks and monitoring.
• Ability to collaborate with data engineers to deliver business insights.

Responsibilities

• Data Pipeline Development: Design, develop, and maintain scalable ETL pipelines using PySpark on CDP.
• Data Ingestion: Manage ingestion from relational DBs, APIs, and files into data lake/warehouse on CDP.
• Data Transformation and Processing: Use PySpark to cleanse and transform large datasets for analytics.
• Performance Optimization: Tune PySpark and CDP for resource efficiency and speed.
• Data Quality and Validation: Implement checks to ensure data accuracy and reliability.
• Automation and Orchestration: Automate data workflows with Oozie or Airflow within CDP.
• Monitoring and Maintenance: Monitor pipelines and troubleshoot issues.

Skills

PySpark

CDP

ETL development

Data pipelines

Big data

Tools

Apache Oozie

Airflow

Job description

Job Descriptions:

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. This role requires a strong background in big data ecosystems, cloud-native tools, and advanced data processing techniques.

The ideal candidate has hands-on experience with data ingestion, transformation, and optimization on the Cloudera Data Platform, along with a proven track record of implementing data engineering best practices. You will work closely with other data engineers to build solutions that drive impactful business insights.

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