Duration: 6 months + extensions
Location: Remote within Spain
Pay Rate: Negotiable
Spanish Speaking
Role Overview:
As a GCP Data Engineer, you will design, build, and manage the end-to-end data architecture on Google Cloud Platform (GCP). You’ll collaborate with data scientists, analysts, and other engineers to ensure data is consistently accessible, clean, and ready for real-time or batch processing. Your responsibilities will span from data ingestion to storage, transformation, and ensuring the scalability of our GCP infrastructure.
Key Responsibilities
- Design and implement ETL/ELT pipelines using GCP services such as BigQuery, Cloud Storage (GCS), Dataflow, and Cloud Functions.
- Develop and manage data pipelines to ingest, process, and store structured and unstructured data from various sources.
- Optimize and scale pipelines to handle large volumes of data efficiently, ensuring low-latency, high-performance data processing.
- Collaborate with cross-functional teams to define data models and ensure data readiness for analytics and reporting.
- Monitor, troubleshoot, and improve data infrastructure using GCP tools such as Cloud Monitoring, Cloud Logging, and Stackdriver.
- Implement data governance, ensuring data quality, integrity, and compliance with industry standards.
- Integrate GCP services with other third-party or on-premises systems to create seamless data workflows.
- Participate in cloud migration projects, assisting in moving existing data infrastructures to GCP.
- Ensure security best practices for managing and accessing data on GCP.
Qualifications
- 3+ years of experience as a Data Engineer, with a focus on Google Cloud Platform (GCP).
- Strong experience with GCP services like BigQuery, Cloud Storage, Cloud Functions, Dataflow, Pub/Sub, and Cloud Composer (Airflow).
- Proficiency in SQL for querying and managing large datasets in BigQuery or similar data warehouses.
- Strong programming skills in Python or Java, with experience automating data pipelines.
- Familiarity with data lakes and data warehousing concepts, including schema design and optimization.
- Understanding of cloud security best practices and data governance on GCP.
- Experience with ETL tools and frameworks for building scalable data pipelines.
- Proven ability to work with CI/CD pipelines and version control systems like Git.
