
Senior Data Architect
1 day ago
The ideal candidate will have experience designing and implementing scalable data and analytics pipelines, enabling production-grade ML systems, and supporting agent-based development leveraging MCP/OpenAPI to MCP wrapper and A2A protocols.
Key Responsibilities
- Data Pipeline Design: Design, build, and maintain scalable data pipelines and ETL/ELT processes for analytics and ML workloads.
- MLOps Frameworks: Implement MLOps frameworks to manage model lifecycle (training, deployment, monitoring, and retraining).
- DevOps Practices: Apply DevOps best practices (CI/CD, containerization, infrastructure as code) to ML and data engineering workflows.
- Data Modeling: Develop and optimize data models, feature stores, and ML serving architectures.
- Model Integration: Collaborate with AI/ML teams to integrate models into production environments.
- Agent Development: Support agent development using MCP/OpenAPI to MCP wrapper and A2A communication protocols.
- Data Quality: Ensure data quality, governance, and compliance with security best practices.
- Troubleshooting: Troubleshoot and optimize data workflows for performance and reliability.
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