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4 days ago
The role of a Cloud Data Engineer involves designing, developing, and maintaining scalable data pipelines and ETL processes using Google Cloud Platform (GCP) services. The ideal candidate will have a strong background in data engineering with a focus on GCP and excellent problem-solving skills.
- Data Pipeline Development: Develop scalable data pipelines and ETL processes using GCP services such as BigQuery, Cloud Data Fusion, Dataflow, Pub/Sub, Cloud Storage, Composer, Cloud Function, and Cloud Run.
- Data Integration: Implement data integration solutions to ingest, process, and store large volumes of structured and unstructured data from various sources.
- Optimization and Troubleshooting: Optimize and tune data pipelines for performance, reliability, and cost-efficiency, ensuring data quality and integrity through data validation, cleansing, and transformation processes.
- Mentorship and Collaboration: Mentor junior data engineers, fostering a culture of knowledge sharing and collaboration.
Candidates for this role should have a degree in Computer Science, Information Technology, or a related field and 4-6 years of experience in data engineering with a strong focus on GCP.
- Qualifications: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- Experience: 4 to 6 years of experience in data engineering with a strong focus on GCP.
- Skills: Proficiency in GCP services such as BigQuery, Cloud Data Fusion, Dataflow, Pub/Sub, Cloud Storage, Composer, Cloud Function, and Cloud Run, strong programming skills in Python and PLSQL, experience with SQL and NoSQL databases, knowledge of data warehousing concepts and best practices, familiarity with data integration tools and frameworks.
This is an excellent opportunity for experienced data engineers to work on the development of scalable data pipelines and ETL processes using GCP services.
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