
Data Engineer (PySpark) - Leading UAE Bank, Cloudera Data Platform Expert
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Job Title: Data Engineer (PySpark)
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About the Role
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, and perform routine maintenance on the Cloudera Data Platform and associated data processes.
⢠Collaboration: Work closely with other data engineers, analysts, product managers, and other stakeholders to understand data requirements and support various data-driven initiatives.
⢠Documentation: Maintain thorough documentation of data engineering processes, code, and pipeline configurations. Qualifications
Education and Experience
⢠Bachelorās or Masterās degree in Computer Science, Data Engineering, Information Systems, or a related field.
⢠3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform. Technical Skills
⢠PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques.
⢠Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase.
⢠Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala).
⢠Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools.
⢠Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks.
⢠Scripting and Automation: Strong scripting skills in Linux. Soft Skills
⢠Strong analytical and problem-solving skills.
⢠Excellent verbal and written communication abilities.
⢠Ability to work independently and collaboratively in a team environment.
⢠Attention to detail and commitment to data quality.
Requirements
- ā¢Bachelorās or Masterās degree in Computer Science, Data Engineering, Information Systems, or related field
- ā¢3+ years of experience as a Data Engineer
- ā¢Strong focus on PySpark and the Cloudera Data Platform
- ā¢Advanced proficiency in PySpark (RDDs, DataFrames, optimization)
- ā¢Strong experience with Cloudera Data Platform (CDP) components
- ā¢Knowledge of data warehousing concepts and ETL best practices
- ā¢Experience with automation and orchestration tools (e.g., Apache Oozie, Airflow)
- ā¢Experience with data quality and validation techniques
Responsibilities
- ā¢Design, develop, and maintain scalable ETL pipelines using PySpark on CDP
- ā¢Implement and manage data ingestion processes
- ā¢Process, cleanse, and transform large datasets using PySpark
- ā¢Conduct performance tuning of PySpark code and Cloudera components
- ā¢Implement data quality checks, monitoring, and validation routines
- ā¢Automate data workflows using orchestration tools
- ā¢Monitor pipeline performance, troubleshoot issues, and perform maintenance
- ā¢Collaborate with stakeholders to understand data requirements
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