Pyspark Data Engineer
VirtusaJobsCloseBy Editorial Insights
Virtusa is seeking a Data Engineer with strong PySpark expertise for a full-time on-site role in Dubai. The ideal candidate will have 8+ years of experience focused on PySpark and the Cloudera Data Platform, with a proven track record of designing, building, and optimizing scalable ETL pipelines, handling data ingestion from diverse sources, and transforming large datasets for analytics. Proficiency with CDP components such as Hive and Impala, data warehousing concepts, and orchestration tools like Airflow or Oozie is essential, as is solid scripting, data quality practices, and collaboration with stakeholders. To apply, tailor your resume to highlight concrete PySpark and CDP wins and quantify your impact, and prepare to discuss end-to-end projects.
Pyspark Data Engineer - (CREQ239015)
Description
Job Title: Data Engineer (PySpark)
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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.
8+ 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.