Cloud Data Architect with AIML

Job Description: education computer science bachelor engineering must from any country does not matter

The contractor will work hands-on to deliver scalable secure and high-performance systems for analytics reporting and machine learning on a petabyte scale.
Requirements:
Cloud Data Architecture Design & Implementation
Must be capable of architecting and building scalable secure cloud-based platforms for analytics reporting data lakes warehouses and machine learning workloads.
Should be able to deliver systems supporting both real-time and batch analytics.
AI/ML Pipeline Development
Required to create deploy and monitor end-to-end AI/ML solutions encompassing data preprocessing modeling inference and solution improvement.
Must automate workflows using MLOps CI/CD and orchestration tools ensuring experimentation scalability and operational efficiency.
Data Modeling Integration and Quality
Must deliver robust data models metadata and taxonomy strategies suitable for large distributed data architectures.
Expected to support and maintain high-quality data integration lineage and lifecycle management processes.
Technology Evaluation and Solutioning
Responsible for researching recommending and implementing appropriate technologies related to cloud big data analytics and ML.
Must be able to lead proofs-of-concept and pilot implementations.
Security Privacy and Compliance
All work must adhere to data security privacy and compliance standards.
Must coordinate with relevant teams to meet regulatory benchmarks and ensure secure compliant solutions.
Technical Collaboration and Documentation
Must collaborate effectively with engineering data science IT and business stakeholders for requirements gathering and solution delivery.
Responsible for producing clear technical documentation diagrams and supporting artifacts.
System Optimization and Troubleshooting
Must monitor and maintain optimal performance and cost-effectiveness of delivered solutions; required to troubleshoot and resolve issues proactively.
Continuous Learning and Innovation
Expected to remain informed about current trends in cloud data and AI/ML and to recommend architectural improvements based on industry best practices.

Minimum Qualifications:
Bachelors degree in computer science required.
At least 5 years of hands-on experience in distributed computing architecture.
Significant hands-on experience in cloud architecture (e.g. AWS Azure GCP) big data platforms and end-to-end data solution workflows.
Demonstrated expertise in machine learning/AI frameworks platforms and MLOps.
Proven record of building optimizing and documenting scalable cloud data and ML solutions.
Ability to diagram architectures at multiple levels of detail ranging from conceptual to detailed implementation.
Ability to document every aspect of work including technical decisions architectures workflows and operational procedures.
Strong skills in technical communication documentation and cross-functional collaboration.

Note:
This contract role is strictly for individual contributors not involving management of staff. Collaboration with internal teams is required but the primary focus is on hands-on independent solution delivery for enterprise-grade data and AI/ML projects.