Data Engineer (PySpark) - Leading UAE Bank, Cloudera Data Platform Expert

GSSTech Group; Dubai; On-site; AED 80,000 - 120,000; Full time

Job summary

An innovative firm is seeking a talented Data Engineer specializing in PySpark and the Cloudera Data Platform. This dynamic role involves designing and maintaining scalable data pipelines that ensure high data quality and availability. You will collaborate with a skilled team to implement best practices in data engineering, focusing on performance optimization and data integrity. The ideal candidate will have a strong background in big data technologies and a passion for transforming raw data into actionable insights. Join this forward-thinking company and make a significant impact on data-driven decisions across the organization.

Qualifications

• 3+ years of experience as a Data Engineer focusing on PySpark and Cloudera.
• Bachelor’s or Master’s degree in relevant field is required.

Responsibilities

• Design and maintain scalable ETL pipelines using PySpark on Cloudera.
• Implement data ingestion and transformation processes for analytics.

Skills

PySpark

Cloudera Data Platform

ETL Pipelines

Data Warehousing

Hadoop

Apache Oozie

Airflow

SQL

Linux Scripting

Data Quality Checks

Education

Bachelor’s or Master’s degree in Computer Science

Degree in Data Engineering or Information Systems

Tools

Cloudera Manager

Hive

Impala

HDFS

HBase

Job description

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

1. 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.
2. 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.
3. Data Transformation and Processing: Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements.
4. Performance Optimization: Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes.
5. Data Quality and Validation: Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline.
6. Automation and Orchestration: Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem.
7. Monitoring and Maintenance: Monitor pipeline performance, troubleshoot issues, and perform routine maintenance on the Cloudera Data Platform and associated data processes.
8. Collaboration: Work closely with other data engineers, analysts, product managers, and other stakeholders to understand data requirements and support various data-driven initiatives.
9. Documentation: Maintain thorough documentation of data engineering processes, code, and pipeline configurations.

Qualifications

Education and Experience

1. Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
2. 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform.

Technical Skills

1. PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques.
2. Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase.
3. Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala).
4. Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools.
5. Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks.
6. Scripting and Automation: Strong scripting skills in Linux.

Soft Skills

1. Strong analytical and problem-solving skills.
2. Excellent verbal and written communication abilities.
3. Ability to work independently and collaboratively in a team environment.
4. Attention to detail and commitment to data quality.