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. 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 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. 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 27,000 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 was founded on principles of equal opportunity for all, and so does not discriminate on the basis of race, religion, color, sex, gender identity, ****** orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.