
Cloud Data Engineer
1 day ago
We are seeking an experienced cloud data architect with a strong background in designing, building, and optimizing scalable data pipelines and architectures on Google Cloud Platform (GCP). The ideal candidate is proficient in GCS, BigQuery, Apache Airflow, and Python, and has expertise in managing complex data workflows and transformations at scale.
- Design and implement highly scalable, reliable, and secure data pipelines on GCP using GCS, BigQuery, and Airflow.
- Develop robust ETL/ELT processes using Python and integrate with data orchestration tools (e.g., Airflow).
- Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions.
- Optimize BigQuery performance through efficient schema design, partitioning, clustering, and query optimization.
- Manage and maintain data lake and data warehouse environments ensuring data integrity and availability.
- Automate and monitor data pipelines to ensure consistent and reliable data delivery.
- Contribute to architecture decisions and ensure adherence to data governance and security standards.
- Mentor junior engineers and promote best practices in data engineering and cloud usage.
Must-Have Skills:
- Google Cloud Platform (GCP): In-depth experience with core services like GCS, BigQuery, IAM, and Cloud Functions.
- BigQuery (BQ): Expertise in data modeling, performance tuning, and large-scale analytics.
- Google Cloud Storage (GCS): Strong understanding of data storage, access patterns, and integration.
- Apache Airflow: Experience in authoring and managing DAGs for complex workflows.
- Python: Proficient in scripting and automation, including working with APIs, data processing libraries (e.g., pandas, PySpark), and custom operators in Airflow.
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