Data Specialist

Job Description

Overall 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. Day-to-Day Activities: Design, develop, and maintain ETL pipelines using PySpark on CDP. Implement and manage data ingestion processes from various sources. Process, cleanse, and transform large datasets using PySpark. Conduct performance tuning and optimization of ETL processes. Implement data quality checks and validation routines. Automate data workflows using orchestration tools. Monitor pipeline performance and troubleshoot issues. Collaborate with team members to understand data requirements. Maintain documentation of data engineering processes and configurations. Show more Show less