Information Technology
Full-Time
MagellanicCloud
Overview
Design, develop, and maintain scalable data pipelines and architectures on GCP.
- Build and optimize ETL/ELT processes to ingest, transform, and load data from diverse sources.
- Develop and maintain data warehousing solutions using Google BigQuery.
- Implement data processing workflows using GCP services such as Dataflow and DataProc.
- Write, optimize, and troubleshoot SQL queries for data manipulation and analysis.
- Develop Python scripts for data processing, automation, and workflow orchestration.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
- Monitor and troubleshoot data pipeline performance, ensuring data quality and reliability.
- Stay up-to-date with the latest GCP technologies and best practices.
- Contribute to the development of data engineering standards and best practices.
- Ensure data security and compliance with relevant Bachelor's degree in Computer Science, Engineering, or a related field.
- 3-5 years of hands-on experience in data engineering.
- 2-3 years of direct experience working with Google Cloud Platform (GCP).
- Strong proficiency in SQL for data manipulation and querying.
- Solid Python development skills for data processing and automation.
- Experience with distributed architectures, ETL/ELT processes, and big data technologies.
- Expertise in Google BigQuery, including data warehousing and query optimization.
- Hands-on experience with GCP services such as Dataflow and DataProc is highly preferred.
- Understanding of data modeling concepts and techniques.
- Experience with data integration tools and technologies.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work independently and as part of a Skills:
- Experience with other GCP services, such as Pub/Sub, Cloud Storage, and Cloud Composer.
- Knowledge of data visualization tools (e.g., Looker, Tableau).
- Experience with infrastructure-as-code tools (e.g., Terraform).
- Familiarity with DevOps practices and CI/CD pipelines.
- Google Cloud Professional Data Engineer certification
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