Back to jobsSenior Data Engineer (PySpark)
Location
United Arab Emirates
Company name
Virtusa
Sector
Technology
Contract duration
Full time
Salary (monthly)
Non-Dislcosed
Experience
3+ Years
About the role
Seeking a Senior Data Engineer to design, develop, and maintain scalable ETL pipelines using PySpark on the Cloudera Data Platform (CDP). Responsibilities include data ingestion from various sources, transformation and processing of large datasets, performance optimization, and ensuring data quality and validation. The role involves automating workflows with tools like Apache Oozie or Airflow, monitoring pipeline performance, and collaborating with cross-functional teams to support data-driven initiatives. Strong expertise in PySpark, Cloudera, and big data technologies is required.
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 (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.
Requirements
- Bachelors or Masters 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.
- 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 SQLbased tools (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.
