Skill: PySpark, hadoop, hive, Hbase, Azure Data
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.
Education and Experience
· 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.
· 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 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.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 36,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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