Distributed Cloud | GCP Data Engineer
Porto, Porto, Portugal
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll bring
All qualificationsCore experience
- Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques.
- Expertise in at least one programming language commonly used for data engineering
- Experience with Infrastructure as Code (IaC) tools like Terraform for automating GCP data infrastructure deployment.
- Solid understanding of distributed systems and ETL/ELT frameworks.
Preferred experience
- Python is highly preferred
- Experience with streaming data technologies and real-time processing within GCP.
- Knowledge of containerization and orchestration (Docker, Kubernetes/GKE).
Qualification wording
Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques.
Expertise in at least one programming language commonly used for data engineering (Python is highly preferred).
Experience with Infrastructure as Code (IaC) tools like Terraform for automating GCP data infrastructure deployment.
Solid understanding of distributed systems and ETL/ELT frameworks.
Experience with streaming data technologies and real-time processing within GCP.
Knowledge of containerization and orchestration (Docker, Kubernetes/GKE).
Tools in this posting
- Python
- SQL
- BigQuery
- Docker
- Google Cloud (GCP)
- Terraform
- Kubernetes
Source — Tool mentions in context
- Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques. - Expertise in at least one programming language commonly used for data engineering (Python is highly preferred). - Experience with Infrastructure as Code (IaC) tools like Terraform for automating GCP data infrastructure deployment.
- Mandatory hands-on expertise with Google Cloud Platform (GCP) data services, including BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Pub/Sub. - Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques. - Expertise in at least one programming language commonly used for data engineering (Python is highly preferred).
We are seeking an experienced and dedicated GCP Data Engineer to join our team. You will be responsible for designing, building, and optimizing robust, scalable, and highly available data pipelines and ETL/ELT solutions exclusively within the Google Cloud Platform (GCP). This role requires a strong focus on utilizing GCP's native data services to ensure data quality, automation, and performance optimization across the data lifecycle. - Design, build, and maintain scalable data pipelines and ETL/ELT processes using core GCP data services such as Cloud Dataflow (Apache Beam), Cloud Dataproc, and BigQuery. - Develop and optimize data infrastructure on GCP to ensure reliable, high-speed data ingestion (e.g., using Cloud Pub/Sub and Cloud Storage).
- Automate deployment, monitoring, and testing of data infrastructure and pipelines using Infrastructure as Code (IaC) tools like Terraform and CI/CD practices. - Manage and optimize GCP data storage solutions, primarily BigQuery (data warehouse) and Cloud Storage (data lake), for performance and cost efficiency. - Provide technical guidance and recommendations on data architecture and technology choices within the GCP ecosystem.
- 3+ years of proven experience as a Data Engineer, focusing heavily on building production-grade data pipelines. - Mandatory hands-on expertise with Google Cloud Platform (GCP) data services, including BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Pub/Sub. - Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques.
- Experience with streaming data technologies and real-time processing within GCP. - Knowledge of containerization and orchestration (Docker, Kubernetes/GKE). Additional Information
Job Description We are seeking an experienced and dedicated GCP Data Engineer to join our team. You will be responsible for designing, building, and optimizing robust, scalable, and highly available data pipelines and ETL/ELT solutions exclusively within the Google Cloud Platform (GCP). This role requires a strong focus on utilizing GCP's native data services to ensure data quality, automation, and performance optimization across the data lifecycle. - Design, build, and maintain scalable data pipelines and ETL/ELT processes using core GCP data services such as Cloud Dataflow (Apache Beam), Cloud Dataproc, and BigQuery.
- Design, build, and maintain scalable data pipelines and ETL/ELT processes using core GCP data services such as Cloud Dataflow (Apache Beam), Cloud Dataproc, and BigQuery. - Develop and optimize data infrastructure on GCP to ensure reliable, high-speed data ingestion (e.g., using Cloud Pub/Sub and Cloud Storage). - Implement data quality checks, monitoring, and validation to ensure accuracy and integrity of data across all GCP systems.
- Manage and optimize GCP data storage solutions, primarily BigQuery (data warehouse) and Cloud Storage (data lake), for performance and cost efficiency. - Provide technical guidance and recommendations on data architecture and technology choices within the GCP ecosystem. Qualifications
- Expertise in at least one programming language commonly used for data engineering (Python is highly preferred). - Experience with Infrastructure as Code (IaC) tools like Terraform for automating GCP data infrastructure deployment. - Solid understanding of distributed systems and ETL/ELT frameworks.
- Collaborate closely with Data Scientists and Data Analysts to ensure data readiness for reporting, analytics, and Machine Learning initiatives (e.g., integrating with Vertex AI). - Automate deployment, monitoring, and testing of data infrastructure and pipelines using Infrastructure as Code (IaC) tools like Terraform and CI/CD practices. - Manage and optimize GCP data storage solutions, primarily BigQuery (data warehouse) and Cloud Storage (data lake), for performance and cost efficiency.
Job description
Job Description
We are seeking an experienced and dedicated GCP Data Engineer to join our team. You will be responsible for designing, building, and optimizing robust, scalable, and highly available data pipelines and ETL/ELT solutions exclusively within the Google Cloud Platform (GCP). This role requires a strong focus on utilizing GCP's native data services to ensure data quality, automation, and performance optimization across the data lifecycle.
Design, build, and maintain scalable data pipelines and ETL/ELT processes using core GCP data services such as Cloud Dataflow (Apache Beam), Cloud Dataproc, and BigQuery.
Develop and optimize data infrastructure on GCP to ensure reliable, high-speed data ingestion (e.g., using Cloud Pub/Sub and Cloud Storage).
Implement data quality checks, monitoring, and validation to ensure accuracy and integrity of data across all GCP systems.
Collaborate closely with Data Scientists and Data Analysts to ensure data readiness for reporting, analytics, and Machine Learning initiatives (e.g., integrating with Vertex AI).
Automate deployment, monitoring, and testing of data infrastructure and pipelines using Infrastructure as Code (IaC) tools like Terraform and CI/CD practices.
Manage and optimize GCP data storage solutions, primarily BigQuery (data warehouse) and Cloud Storage (data lake), for performance and cost efficiency.
Provide technical guidance and recommendations on data architecture and technology choices within the GCP ecosystem.
Qualifications
- 3+ years of proven experience as a Data Engineer, focusing heavily on building production-grade data pipelines.
Mandatory hands-on expertise with Google Cloud Platform (GCP) data services, including BigQuery, Cloud Dataflow, Cloud Storage, and Cloud Pub/Sub.
Strong proficiency in SQL and extensive experience with data warehousing concepts and data modeling techniques.
Expertise in at least one programming language commonly used for data engineering (Python is highly preferred).
Experience with Infrastructure as Code (IaC) tools like Terraform for automating GCP data infrastructure deployment.
Solid understanding of distributed systems and ETL/ELT frameworks.
Excellent analytical and problem-solving skills, with a passion for continuous learning and data governance.
Preferred Skills:
Google Certified Professional Data Engineer certification.
Experience with streaming data technologies and real-time processing within GCP.
Knowledge of containerization and orchestration (Docker, Kubernetes/GKE).
Additional Information
The Devoteam Group works for equal opportunities, promoting its employees based on merit and actively fights against all forms of discrimination. We are convinced that diversity contributes to the creativity, dynamism and excellence of our organization. All of our vacancies are open to people with disabilities.
Company Description
At Devoteam, we believe that technology with strong human values can actively drive change for the better. Discover how Tech for People unlocks the future, creating a positive impact on the people and the world around us. We are a global leading player in Digital Transformation for leading organisations across EMEA, with a revenue of €1B. We believe in transforming technology to create value for our clients, partners and employees in a world where technology is developed for people. We are proud of the culture we have built together. We are proud of our people at the service of technology. We are proud of our diverse environment. Because we are #TechforPeople. Join our multidisciplinary team of Cloud experts, Designers, Business consultants, Security experts, Engineers, Developers and other extraordinary talents, spread across more than 20 EMEA countries. Become one of our +10.000 tech and business leaders on cloud, data and cyber security. Let’s fuse creativity with technology together and build innovative solutions that actively change things for the better.
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Source & posting history
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- Pay
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- Location & working pattern
Porto, Porto, Portugal
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- Status in our records
- Active
- First seen by us
- May 13, 2026
- Recorded sightings
- 382
- Last seen by us
- Oct 11, 2026
- Employer says posted
- Oct 10, 2025
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