Data Engineer
1 month ago
Skills :
- Hadoop
- Python
- Spark
- PySpark
- ETL (Extract, Transform, Load)
Roles & Responsibilities :
- Data Ingestion: Develop and maintain data pipelines for ingesting raw data from various sources into the Hadoop ecosystem.
- Data Processing: Utilize Python and Spark to process and transform large volumes of data efficiently, ensuring scalability and performance.
- Data Modeling: Design and implement data models that facilitate efficient querying and analysis of structured and unstructured data.
- ETL Development: Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and integrate data from different sources into data warehouses or data lakes.
- Performance Tuning: Optimize data processing workflows and queries to improve performance and reduce processing times.
- Data Quality Assurance: Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data.
- Data Governance: Enforce data governance policies and standards to ensure compliance with regulatory requirements and industry best practices.
- Documentation: Maintain documentation for data pipelines, data models, and ETL processes to facilitate knowledge sharing and troubleshooting.
- Collaboration: Collaborate with cross-functional teams including data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
- Continuous Improvement: Stay updated with emerging technologies and best practices in data engineering, and proactively identify opportunities for process optimization and automation.
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