We are HCLTech, one of the fastest-growing large tech companies in the world and home to 219,000+ people across 54 countries, supercharging progress through industry-leading capabilities centered around Digital, Engineering and Cloud.
The driving force behind that work, our people, are diverse, creative, and passionate, raising the bar for excellence on a regular basis. We, in turn, work hard to bring out the best in them as we strive to help them find their spark and become the best version of themselves that they can be.
We are on the lookout for a highly talented and self-motivated Pyspark Data Engineer to join us on our journey in advancing the technological world through innovation and creativity.
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: -
Technical Skills: -
Soft Skills: -
Why Us: -
We are one of the fastest-growing large tech companies in the world, with offices in 50+ countries across the globe and 219,000 employees,
Equality & Opportunity for All: -
Representing 165 nationalities across the globe, we pride ourselves on being an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law.