Data Engineer (PySpark) - Leading UAE Bank, Cloudera Data Platform Expert job opportunity at GSSTech Group.

Home Jobs In United Arab Emirates Tag: Cloudera Data Platform Expert Data Engineer (PySpark) - Leading UAE Bank, Cloudera Data Platform Expert position at GSSTech Group


Date2026-01-27T08:17:36.221Z bot
GSSTech Group Data Engineer (PySpark) - Leading UAE Bank, Cloudera Data Platform Expert
Experience: 3-years
Pattern: full-time
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Cloudera Data Platform Expert

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degreeAssociate
loacation Dubai, United Arab Emirates
loacation Dubai....United Arab Emirates

Job Title: Data Engineer (PySpark) ________________________________________ 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 Bachelor’s or Master’s 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.

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