Design, build, and maintain scalable ETL/ELT data pipelines and BigQuery data models. Implement Airflow workflows, CI/CD for deployments, ensure data quality and performance, and collaborate with data scientists, analysts, and business teams to deliver reliable analytics-ready data.
We are looking for a skilled Data Engineer with strong experience in building, optimizing, and maintaining scalable data platforms and pipelines. The ideal candidate will work closely with data scientists, analysts, and business teams to ensure reliable, high-quality data delivery across analytics and reporting use cases.
Key Skills & Technologies- 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
- 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
Graduate in Data Science, Computer Science, Statistics, or a related field. 3-4 years of experience in data science or data analysis.
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