About
Design, develop, and maintain scalable and reliable data pipelines Build and optimize ETL/ELT processes to ingest data from multiple sources Develop and manage data models in BigQuery to support analytics and reporting Implement automated workflows and scheduling using Airflow Ensure data quality, integrity, and performance across pipelines Collaborate with cross-functional teams to gather requirements and deliver data solutions Apply CI/CD best practices to support efficient and reliable deployments Troubleshoot and resolve data pipeline and performance issues Requirements:
Graduate in Data Science, Computer Science, Statistics, or a related field. 3-4 years of experience in data science or data analysis. Strong programming experience in Python and SQL. Hands-on experience with Google Cloud Platform (GCP) services. Expertise in BigQuery for data warehousing, performance tuning, and cost optimization. Experience with ETL/ELT frameworks and large-scale data pipeline development. Workflow orchestration using Apache Airflow. CI/CD implementation for data pipelines using tools like Git, Jenkins, or Cloud Build. Solid understanding of data modeling, partitioning, and schema design. Experience with cloud storage, data validation, and monitoring. Knowledge of containerization (Docker) and basic DevOps practices is a plus.
Languages
- English
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