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Enterprise Data Pipeline Architect
1 week ago
About the Role
We are seeking an Enterprise Data Pipeline Architect to join our team at MWIDM Staffing Services. The ideal candidate will have a strong background in designing, developing, and maintaining efficient and reliable data pipelines using PySpark. They will be responsible for implementing ETL processes to ingest, transform, and load data from various sources, optimizing PySpark code for performance and scalability, and working with large datasets and distributed computing frameworks.
Key Responsibilities:
- Design, develop, and maintain efficient and reliable data pipelines using PySpark.
- Implement ETL processes to ingest, transform, and load data from various sources.
- Optimize PySpark code for performance and scalability.
- Work with large datasets and distributed computing frameworks.
- Develop and maintain data quality checks and monitoring processes.
- Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver data solutions.
- Build and deploy data pipelines to production environments.
- Troubleshoot and debug data pipeline issues.
Requirements:
- 5+ years of experience in data engineering.
- Strong proficiency in Python and PySpark.
- Deep understanding of Spark architecture and its core components.
- Experience with data warehousing concepts and dimensional modeling.
- Proficiency in SQL and experience writing complex queries.
- Experience with data ingestion tools and techniques.
- Experience with data transformation and cleansing.
- Experience with data quality monitoring and validation.
- Experience with workflow management tools (Airflow, Luigi).
- Experience with version control systems (Git).