Data engineer- Data platforms (GCP) expérimenté H/F - IBM Client Innovation Center
IBM · Bois-Colombes, Île-de-France, France
- On site
- Full-time
- $120,000 / year
- Bois-Colombes, Île-de-France, France
Job highlights
- Design scalable GCP data pipelines.
- Implement ETL/ELT workflows using Cloud tools.
- Deploy ML models and build APIs.
- Develop microservices and ensure CI/CD.
- Collaborate and mentor junior engineers.
About the role
About IBM Consulting
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide.
You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact.
At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
Your Role And Responsibilities
We are looking for motivated and talented leaders to join our technical capabilities for innovative projects and contribute to a unique structure. In this role, you will be a major player at all stages of our various projects and will have the following missions:
- Design and develop scalable data pipelines, in batch and real-time, on GCP.
- Implement ETL/ELT workflows using tools such as Cloud Workflows and Cloud Pub/Sub.
- Design dimensional data models and curated data marts.
- Deploy and manage Machine Learning models with Vertex AI and build real-time inference APIs.
- Develop and deploy microservices in Python/Node.js on Cloud Run or Google Kubernetes Engine.
- Implement best practices for CI/CD, infrastructure as code, monitoring, and security.
- Ensure data governance, access control, and cost optimization.
- Collaborate with cross-functional teams and mentor junior engineers.
Required Technical And Professional Expertise
- Over 5 years of experience in data engineering and cloud environments.
- Solid hands-on experience with Google Cloud Platform and designing cloud-native architectures.
- Excellent understanding and mastery of IT architectures, with the ability to design scalable, secure, and high-performance solutions.
- Strong proficiency in Python and advanced SQL expertise.
- Solid experience in data modeling, ETL/ELT processes, and enterprise data warehousing.
- Expertise in data science methodologies, including data cleaning, exploration, and visualization principles.
- Experience in deploying AI/ML models and creating REST APIs in production environments.
- Good understanding of distributed systems and microservices architectures.
- Experience in containerization (Docker), CI/CD pipelines, and Infrastructure as Code.
- Excellent problem-solving skills and strong analytical mindset.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Ability to work autonomously and manage time effectively in a dynamic and evolving environment.
- Collaborative spirit, with proven experience working in cross-functional teams.
- Adaptability and willingness to quickly learn new technologies and methodologies.
- Fluency in French and English, written and spoken.
Key skills/competency
- Data Engineering
- Google Cloud Platform (GCP)
- Python
- SQL
- ETL/ELT
- Data Modeling
- Machine Learning (ML)
- Microservices
- CI/CD
- Cloud Architecture
Skills & topics
- Data Engineer
- GCP
- Data Pipelines
- ETL
- ELT
- Python
- SQL
- Data Modeling
- Cloud Architecture
- Machine Learning
- Vertex AI
- Microservices
- Google Cloud Platform
- IBM Consulting
- Data Science
How to get hired
- Tailor your resume: Highlight your 5+ years of data engineering experience, GCP expertise, and Python/SQL skills.
- Showcase cloud architecture: Emphasize your experience designing scalable, secure, and high-performance solutions on GCP.
- Demonstrate ML and API skills: Detail your experience deploying AI/ML models and building production-ready REST APIs.
- Highlight collaboration: Mention your experience in CI/CD, IaC, and working with cross-functional teams.
- Prepare for interviews: Be ready to discuss complex technical concepts and problem-solving scenarios.
Technical preparation
Master Python and advanced SQL for data manipulation.,Practice designing scalable GCP data pipelines.,Build CI/CD pipelines and IaC for cloud deployment.,Develop and deploy ML models and REST APIs.
Behavioral questions
Describe a complex data problem you solved.,How do you mentor junior engineers effectively?,Explain a technical concept to a non-technical person.,How do you handle evolving project requirements?
Frequently asked questions
- What are the key technical skills required for the Data Engineer role at IBM?
- The Data Engineer role at IBM emphasizes over 5 years of experience in data engineering and cloud environments, with a strong focus on Google Cloud Platform (GCP). Key technical skills include Python, advanced SQL, data modeling, ETL/ELT processes, enterprise data warehousing, AI/ML model deployment, REST API creation, containerization (Docker), CI/CD pipelines, and Infrastructure as Code.
- What is the expected experience level for this Data Engineer position at IBM?
- IBM is seeking experienced professionals for this Data Engineer role, requiring over 5 years of dedicated experience in data engineering and cloud environments. The description also mentions the ability to mentor junior engineers, indicating a need for leadership potential and experience.
- What kind of data pipelines will I be working on as a Data Engineer at IBM?
- As a Data Engineer at IBM, you will be responsible for designing and developing scalable data pipelines, encompassing both batch and real-time processing on Google Cloud Platform (GCP). You will also implement ETL/ELT workflows using tools like Cloud Workflows and Cloud Pub/Sub.
- Does IBM offer opportunities for career growth and learning for Data Engineers?
- Yes, IBM Consulting fosters a culture of growth and empathy, focusing on long-term career development. They encourage challenging the norm, exploring new ideas, and learning new technologies and methodologies. You will also have opportunities to mentor junior engineers.
- What is the role of Machine Learning and APIs in this Data Engineer position?
- This Data Engineer role involves deploying Machine Learning models using Vertex AI and building real-time inference APIs. You will also be responsible for developing and deploying microservices that may interact with these ML models or APIs in production environments.
- What is the expected work arrangement for this Data Engineer role at IBM?
- While the job description doesn't explicitly state the work arrangement, IBM Consulting emphasizes worldwide collaboration. Given the nature of consulting and the mention of various project stages, it's likely to be a hybrid or on-site role, potentially with opportunities for remote work depending on project needs and location.
- What kind of projects can I expect to work on as a Data Engineer with IBM?
- You will work on innovative projects for leading companies across industries, helping them shape their hybrid cloud and AI journeys. This involves designing and developing data platforms, implementing data pipelines, deploying ML models, and building microservices on GCP.