Data Architect

RESPONSIBILITIES:

1. Define, develop, manage & sustain core components of the data platform, such as:
   • Multi-tenant data collection and storage
   • Multi-tenant streaming and data processing
   • Shared data model, including NoSQL modeling
   • Data management and security components
   • Multi-tenant and customizable analytical dashboards
2. Develop IT solutions with partners (startups, IT companies, other industrial companies, suppliers, universities, research institutes) to package Software as a Service (SaaS) offering along a technical team of Data/DevOps engineers.
3. Lead the design and architecture deployment of next-generation data solutions within a lean startup pathway, collaborating with data engineers, DevOps, engineering & mobility experts, data scientists, software engineers & HMI designers.
4. Understand customer needs and provide an architecture design to meet these requirements.
5. Own the overall technical vision of the solution regarding scalability, security, performance, reliability, and recovery.
6. Build multi-tenant streaming and data processing capabilities in batch and near-real-time flows.
7. Evaluate the opportunities from emerging technologies.
8. Apply strong testing and quality assurance practices.

EDUCATION :

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Preferred:Data Science and/or Machine Learning, Cybersecurity.

Competencies & Skills:

• Extensive knowledge of data modeling, analytics, and software architecture (preferably Java and Python).
• Proven experience in designing and developing scalable solutions with data processing engines for production environments (e.g., Apache Spark).
• Experience in various data management platforms and cloud technologies (e.g., Apache NIFI, Kubernetes, Docker, Elasticsearch).
• Experience in designing databases MySQL, PostgreSQL, Cassandra, MongoDB and eliminating performance bottlenecks.
• Knowledge of cloud technologies (Azure, AWS, GCP), msfabric, lakehouse, deltalake
• Knowledge of data science/machine learning or experience designing data pipelines for ML models.
• Knowledge of network and security:SSL, certificates, IPSEC, Active Directory, LDAP.
• Experience using data governance tools:Collibra, Apache Atlas.
• Knowledge of the Elastic/ELK stack.
• Knowledge about Machine Learning with scikit-learn, R, Tensorflow, or another AI framework or toolkit.
• Proven experience in deploying and maintaining solutions on cloud and/or on-premise environments.
• Proven experience in providing technical guidance to teams.
• Proven experience in managing customer expectations.
• Proven track record of driving decisions collaboratively, resolving conflicts, and ensuring follow-through.
• Extensive knowledge of data processing and software development, in Python or Java/Scala environment.
• Proven experience in designing stable solutions, testing, and debugging.
• Demonstrated technical guidance with worldwide teams.
• Demonstrated teamwork and collaboration in a professional setting.
• Proven capabilities with worldwide teams.
• Proficient in English; proficiency in French is a plus.

Performance Measurements:

• On-Time Delivery (OTD)
• Developments Quality, Cost, and Delivery (QCD)