Job Description:
Duration : 6 Months

Data Modeling & AI Engineer
• Focus: IT/Cloud Layer: Design and implement scalable data products and modern cloud-based data architecture, ensuring robust data governance and quality.
• Creating, automating, and maintaining complex data models across enterprise and cloud platforms to support Digital Transformation.
• Developing, training, and deploying AI/ML/LLM models to extract insights and drive process optimization.
• Full-stack development to build and maintain data visualization and user-facing applications.
• Leverage and integrate with the Skywise platform for data ingestion, analytics, and service development.
• Managing and organizing data systems for multi-disciplinary teams from start to finish.

Required skills and experience:
• Data Management Engineering: Experience in structuring, managing, and maintaining complex data systems for multi-disciplinary teams.
• Programming: Proficient in Python (high priority for data science/AI) and associated data/AI libraries. Knowledge of other languages like C++ is an asset.



Strong OOPs understanding.
• Data Management: Expertise in cloud data platforms (GCP/AWS/Azure), big data technologies, and building data lakes/warehouses. Solid database development experience (SQL/NoSQL).
• Software Architecture: Deployment experience (Docker, CI/CD Pipelines, Maintenance). Experience with MLOps principles.
• Version Control & Collaboration: Experienced with Git/GitLab, working in Agile environments.
• Requirements Management: Skilled in gathering and managing complex stakeholder requirements for data products and AI solutions.
• Agile Experience: Comfortable working in Agile teams, iterating on data and system models.
• Connectivity Concepts: Highly proficient in API integration, microservices architecture, HTTP methods, and full-stack client-server communication for data product delivery.
• Communication Skills: Clear communicator, able to convey complex technical concepts to diverse a

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