Job Title: Cloud Data Architect with AIML
Location: San Jose, CA (100% on-site)
Job Type: Contract
Job Description:
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.
AIML Pipeline Development
Required to create, deploy, and monitor end-to-end AIML solutions, encompassing data preprocessing, modeling, inference, and solution improvement.
Must automate workflows using MLOps, CICD, 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 AIML and to recommend architectural improvements based on industry best practices.
Minimum Qualifications:
Bachelor s 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, Google Cloud Platform), big data platforms, and end-to-end data solution workflows.
Demonstrated expertise in machine learningAI 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.
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