Data Cloud Engineer GCP (H/F) at Devoteam

📍 Job Overview

Job Title: Data Cloud Engineer GCP (H/F)
Company: Devoteam
Location: Levallois-Perret, Ile-de-France, France
Job Type: On-site
Category: DevOps Engineer
Date Posted: 2025-07-29
Experience Level: Mid-Senior level (2-5 years)
Remote Status: On-site

🚀 Role Summary

Design and deploy robust data solutions on Google Cloud Platform (GCP) using services like BigQuery, Dataflow, and Cloud Storage.
Ensure optimal architecture and infrastructure by providing assistance and expertise to clients.
Collaborate with CloudOps teams to build solid foundations for GCP adoption.
Manage incidents, requests, and participate in on-call rotations to ensure service availability and reliability.

📝 Enhancement Note: This role focuses on GCP data services, requiring a strong understanding of cloud infrastructure and data management. Candidates should be comfortable working with various GCP services and have experience in data engineering or a related field.

💻 Primary Responsibilities

Solution Design & Deployment: Design and deploy data solutions on GCP using services such as BigQuery, Dataflow, and Cloud Storage. Ensure data integrity, security, and performance.
Security & Monitoring: Integrate security, monitoring, alerting, and access control into data solutions. Monitor data pipelines and ensure data quality.
Automation: Automate deployment, patching, and provisioning processes using tools like Terraform. Implement CI/CD pipelines for efficient and reliable data processing.
Client Assistance: Provide assistance and expertise to clients, helping them understand and adopt GCP services. Conduct workshops, training, and create clear documentation.
Incident Management: Manage incidents, requests, and participate in on-call rotations to ensure service availability and reliability. Collaborate with CloudOps teams to resolve issues promptly.

📝 Enhancement Note: This role requires strong problem-solving skills and the ability to work effectively with both technical and non-technical stakeholders. Candidates should be comfortable working in a dynamic environment and adapting to changing priorities.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant certifications (e.g., Google Cloud Certified - Professional Data Engineer) are a plus.

Experience: Proven experience (2-5 years) in data engineering, cloud engineering, or a related role. Experience with GCP data services is required.

Required Skills:

Proficiency in GCP data services (BigQuery, Dataflow, Cloud Storage, Pub/Sub, etc.)
Strong programming skills in Python, Scala, Java, or other relevant languages
Experience with Infrastructure as Code (IaC) tools, preferably Terraform
Familiarity with Linux and Kubernetes
Agile methodologies and ITIL V4 certification
Strong communication and collaboration skills in English and French

Preferred Skills:

Experience with data warehousing, ETL/ELT processes, and data modeling
Familiarity with data visualization tools (e.g., Looker, Tableau)
Knowledge of data governance and data quality principles
Experience with cloud security best practices and compliance frameworks

📝 Enhancement Note: Candidates should have a strong foundation in data engineering principles and be comfortable working with large datasets. Experience with data pipelines, data transformation, and data analysis is a plus.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate experience with GCP data services and infrastructure projects.
Showcase projects that highlight data modeling, ETL/ELT processes, and data visualization.
Include live demos and case studies that showcase your problem-solving skills and ability to optimize data processing.

Technical Documentation:

Document your approach to data architecture, data quality, and data governance.
Explain your methodology for data transformation, data analysis, and data visualization.
Describe your experience with incident management, on-call rotations, and service reliability.

📝 Enhancement Note: Candidates should emphasize their ability to design and deploy robust data solutions, as well as their experience working with clients to optimize GCP adoption.

💵 Compensation & Benefits

Salary Range: €45,000 - €60,000 per year (based on experience and market research)

Benefits:

Competitive health insurance and retirement plans
Training and development opportunities, including access to Google Cloud training and certifications
Flexible working hours and remote work options (after a probation period)
A dynamic and collaborative work environment with a strong focus on learning and growth

Working Hours: 40 hours per week, with flexible hours and the possibility of remote work after the probation period.

📝 Enhancement Note: The salary range is based on market research for mid-senior level data engineers in the Paris region. Benefits and working hours are subject to change and may vary based on the company's policies and the candidate's experience and qualifications.

🎯 Team & Company Context

🏢 Company Culture

Industry: Devoteam is a global consultancy firm focused on digital transformation, with a strong presence in the cloud computing sector. They work with clients across various industries, helping them adopt and integrate new technologies to drive business growth.

Company Size: Medium-sized company with around 20,000 employees worldwide. This size allows for a structured approach to career development while maintaining a dynamic and agile work environment.

Founded: 1990, with the Devoteam G Cloud division established in 2009 to focus on Google Cloud services.

Team Structure:

The data cloud engineering team works closely with cloud operations (CloudOps) teams to ensure optimal infrastructure and service reliability.
The team is structured around specific GCP services, with each member specializing in one or more services (e.g., BigQuery, Dataflow, Cloud Storage).
The team follows an Agile/Scrum methodology, with regular sprint planning, code reviews, and quality assurance processes.

Development Methodology:

Agile/Scrum methodologies are used for project management and software development.
Code reviews, testing, and quality assurance processes are in place to ensure code quality and maintainability.
Deployment strategies, CI/CD pipelines, and automated testing are used to ensure efficient and reliable data processing.

Company Website: Devoteam G Cloud

📝 Enhancement Note: Devoteam's culture emphasizes collaboration, innovation, and continuous learning. The company invests heavily in training and development opportunities to help employees grow both personally and professionally.

📈 Career & Growth Analysis

Web Technology Career Level: Mid-Senior level data engineer, responsible for designing and deploying robust data solutions on GCP. This role requires a strong understanding of cloud infrastructure, data management, and data engineering principles.

Reporting Structure: The data cloud engineer reports directly to the data cloud engineering manager and works closely with the cloud operations (CloudOps) team to ensure optimal infrastructure and service reliability.

Technical Impact: This role has a significant impact on data processing, data quality, and data governance. The data cloud engineer plays a crucial role in ensuring optimal architecture and infrastructure for GCP adoption, enabling clients to make data-driven decisions and improve their business outcomes.

Growth Opportunities:

Technical Specialization: Deepen expertise in specific GCP data services or related technologies (e.g., data warehousing, data lakes, or data governance).
Technical Leadership: Develop leadership skills by mentoring junior team members, leading projects, or contributing to the development of best practices and standards.
Architecture & Design: Expand responsibilities to include architecture and design decisions, working with stakeholders to define data strategy and roadmaps.

📝 Enhancement Note: This role offers significant opportunities for career growth and development within the data engineering and cloud computing fields. Candidates should be eager to learn and take on new challenges to maximize their potential for growth.

🌐 Work Environment

Office Type: Modern, collaborative office space designed to facilitate teamwork and innovation. The office includes dedicated workspaces, meeting rooms, and breakout areas.

Office Location(s): Levallois-Perret, Ile-de-France, France. The office is easily accessible by public transportation, with nearby amenities and restaurants.

Workspace Context:

The workspace is designed to encourage collaboration and knowledge sharing, with open-plan offices and dedicated team spaces.
Each workstation is equipped with multiple monitors, testing devices, and high-speed internet access to support efficient data processing and analysis.
The workspace includes dedicated areas for quiet work, meetings, and informal discussions, allowing team members to choose the environment that best suits their needs.

Work Schedule: The standard workweek is Monday to Friday, with flexible hours and the possibility of remote work after the probation period. Working hours are typically 9:00 AM to 6:00 PM, with a one-hour lunch break.

📝 Enhancement Note: The work environment at Devoteam is designed to support collaboration, innovation, and continuous learning. The company encourages a healthy work-life balance and provides the resources and support necessary for employees to succeed in their roles.

📄 Application & Technical Interview Process

Interview Process:

Technical Phone Screen: A 30-minute phone or video call to assess your understanding of GCP data services and data engineering principles. Be prepared to discuss your experience with data pipelines, data transformation, and data analysis.
On-site Technical Interview: A half-day on-site interview consisting of a technical deep dive, system design discussion, and cultural fit assessment. You will be asked to present your portfolio and demonstrate your problem-solving skills through coding challenges and architecture discussions.
Final Evaluation: A final evaluation based on your performance in the technical interview, cultural fit, and alignment with the company's values and goals.

Portfolio Review Tips:

Highlight your experience with GCP data services and infrastructure projects.
Include live demos and case studies that showcase your problem-solving skills and ability to optimize data processing.
Explain your approach to data architecture, data quality, and data governance.
Emphasize your experience working with clients to optimize GCP adoption and ensure data-driven decision-making.

Technical Challenge Preparation:

Brush up on your knowledge of GCP data services, data engineering principles, and data analysis techniques.
Practice coding challenges and architecture discussions to refine your problem-solving skills and communication abilities.
Familiarize yourself with Devoteam's company culture, values, and mission to ensure a strong cultural fit.

ATS Keywords: GCP, BigQuery, Dataflow, Cloud Storage, Terraform, Linux, Kubernetes, Python, Scala, Java, Agile, ITIL V4, Data Engineering, Cloud Engineering, Data Warehousing, ETL/ELT, Data Modeling, Data Visualization, Incident Management, On-Call Rotation, Service Reliability, Data Quality, Data Governance, Data Analysis, Data Transformation, Data Pipeline, Cloud Security, Compliance Frameworks, Technical English, French.

📝 Enhancement Note: The interview process at Devoteam is designed to assess your technical skills, problem-solving abilities, and cultural fit. Candidates should be prepared to discuss their experience with GCP data services, data engineering principles, and data analysis techniques.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: Not applicable for this role.

Backend & Server Technologies:

GCP Data Services: BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Functions, Cloud Composer, and other relevant GCP services.
Infrastructure Tools: Terraform for Infrastructure as Code (IaC), Google Cloud Shell for command-line interface, and Google Cloud Console for web-based interface.

Development & DevOps Tools:

Version Control: Git and GitHub for collaborative development and code reviews.
CI/CD Pipelines: GitHub Actions, Cloud Build, and Cloud Functions for automated deployment and testing.
Monitoring Tools: Stackdriver Monitoring, Cloud Logging, and Cloud Audit Logs for infrastructure and data pipeline monitoring.

📝 Enhancement Note: This role requires a strong understanding of GCP data services and infrastructure tools. Candidates should be comfortable working with various GCP services and have experience with data engineering or a related field.

👥 Team Culture & Values

Web Development Values:

Innovation: Devoteam encourages continuous learning and innovation, with a strong focus on staying up-to-date with the latest technologies and best practices.
Collaboration: The company emphasizes teamwork and collaboration, with a structured approach to knowledge sharing and mentoring.
Expertise: Devoteam values deep technical expertise and encourages employees to develop their skills and specialize in specific areas of interest.
Client Focus: The company is committed to delivering exceptional client experiences and ensuring client success through data-driven decision-making and optimized GCP adoption.

Collaboration Style:

Cross-Functional Integration: The data cloud engineering team works closely with cloud operations (CloudOps) teams to ensure optimal infrastructure and service reliability.
Code Review Culture: The team follows Agile/Scrum methodologies, with regular code reviews and quality assurance processes to ensure code quality and maintainability.
Knowledge Sharing: Devoteam encourages a culture of knowledge sharing and mentoring, with regular training sessions, workshops, and brown-bag lunches.

📝 Enhancement Note: Devoteam's culture is built on a foundation of collaboration, innovation, and continuous learning. The company invests heavily in training and development opportunities to help employees grow both personally and professionally.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Pipeline Optimization: Design and optimize data pipelines to ensure efficient and reliable data processing, with a focus on minimizing latency and maximizing throughput.
Data Transformation & Analysis: Develop and implement data transformation and analysis techniques to extract insights from large datasets, enabling data-driven decision-making and business growth.
Data Governance & Quality: Ensure data quality and governance by implementing best practices for data modeling, data validation, and data lineage. Collaborate with stakeholders to define data governance policies and standards.
Cloud Security & Compliance: Implement cloud security best practices and ensure compliance with relevant regulations and standards. Collaborate with stakeholders to define security policies and procedures.

Learning & Development Opportunities:

Technical Skill Development: Deepen your expertise in specific GCP data services or related technologies (e.g., data warehousing, data lakes, or data governance).
Certification & Training: Pursue relevant certifications (e.g., Google Cloud Certified - Professional Data Engineer) and participate in training sessions, workshops, and webinars to stay up-to-date with the latest technologies and best practices.
Mentorship & Leadership: Seek mentorship opportunities to develop your leadership skills and contribute to the development of best practices and standards within the data engineering and cloud computing fields.

📝 Enhancement Note: This role offers significant opportunities for technical growth and development within the data engineering and cloud computing fields. Candidates should be eager to learn and take on new challenges to maximize their potential for growth.

💡 Interview Preparation

Technical Questions:

Data Engineering Principles: Explain your understanding of data engineering principles, data pipelines, and data transformation techniques. Be prepared to discuss your experience with data modeling, data warehousing, and ETL/ELT processes.
GCP Data Services: Demonstrate your proficiency with GCP data services, including BigQuery, Dataflow, Cloud Storage, and Pub/Sub. Be prepared to discuss your experience with data analysis, data visualization, and data governance.
Architecture & Design: Explain your approach to data architecture and design, with a focus on optimizing data processing, data quality, and data governance. Be prepared to discuss your experience with incident management, on-call rotations, and service reliability.

Company & Culture Questions:

Company Culture: Explain what you understand about Devoteam's company culture, values, and mission. Be prepared to discuss how your personal values and work style align with the company's culture and goals.
Data-Driven Decision-Making: Describe your experience working with clients to optimize GCP adoption and ensure data-driven decision-making. Be prepared to discuss your approach to data analysis, data visualization, and data storytelling.
Technical Leadership: Explain your approach to technical leadership, mentoring, and knowledge sharing. Be prepared to discuss your experience with architecture and design decisions, project management, and stakeholder communication.

Portfolio Presentation Strategy:

Live Demos: Prepare live demos of your GCP data services and infrastructure projects, highlighting your problem-solving skills and ability to optimize data processing.
Case Studies: Develop case studies that showcase your experience with data modeling, ETL/ELT processes, and data analysis. Include data visualizations and data storytelling to illustrate your findings and recommendations.
Code Explanation: Be prepared to explain your code and architecture decisions, demonstrating your understanding of data engineering principles and GCP best practices.

📝 Enhancement Note: The interview process at Devoteam is designed to assess your technical skills, problem-solving abilities, and cultural fit. Candidates should be prepared to discuss their experience with GCP data services, data engineering principles, and data analysis techniques.

📌 Application Steps

To apply for this data cloud engineer GCP (H/F) position at Devoteam:

Tailor Your Resume: Highlight your experience with GCP data services, data engineering principles, and data analysis techniques. Include relevant keywords and phrases to optimize your resume for Applicant Tracking Systems (ATS).
Prepare Your Portfolio: Include live demos and case studies that showcase your problem-solving skills and ability to optimize data processing. Emphasize your experience with data modeling, ETL/ELT processes, and data analysis.
Practice Coding Challenges: Brush up on your knowledge of GCP data services, data engineering principles, and data analysis techniques. Practice coding challenges and architecture discussions to refine your problem-solving skills and communication abilities.
Research the Company: Familiarize yourself with Devoteam's company culture, values, and mission. Understand their approach to data-driven decision-making and GCP adoption to ensure a strong cultural fit.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Data Cloud Engineer GCP (H/F)