Senior Palantir Platform Architect

Work Mode: Hybrid, with some overlap with Global teams

Boston Scientific is seeking an Enterprise Data Platform Architect to design, govern, and support a shared enterprise data and analytics platform used by multiple projects and product teams.

This is a senior hands‑on technical role focused on data platform architecture, semantic data modeling, enterprise integration, security, governance, CI/CD, observability, and production support.

• Design and evolve the enterprise data and AI platform for use across multiple teams and projects.
• Define architecture standards for the semantic data model, data pipelines, applications, APIs, and integrations.
• Build reusable platform patterns, templates, APIs, and components to accelerate delivery.
• Design integrations with Snowflake, AWS, Azure, databases, APIs, SaaS platforms, and internal systems
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• Establish platform governance for access controls, security, data protection, auditability, and compliance
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• Define CI/CD, release management, testing, and deployment standards across environments.
• Implement observability through logging, metrics, lineage, alerting, and operational dashboards.
• Provide hands‑on support for production issues, troubleshooting, performance, and root‑cause analysis
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• Guide project teams on platform architecture, best practices, and reusable platform capabilities.
• Partner with Cybersecurity, Data Governance, Enterprise Architecture, and engineering teams.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
• Strong hands‑on experience with enterprise data and analytics platforms and enterprise‑scale implementations.
• Experience with semantic data modeling, data pipelines, APIs, and enterprise integrations.
• Strong Python and SQL skills.
• Working knowledge of Model Context Protocol (MCP), including MCP-based integration patterns, tool connectivity, security, and governance.
• Experience with CI/CD, release management, security, governance, observability, and production support
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• Experience integrating platforms such as Snowflake, AWS, Azure, databases, APIs, and SaaS applications
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• Experience supporting shared platforms used by multiple projects or product teams
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• Willingness to work with some overlap with US business hours
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• Experience with enterprise GenAI / AI platform capabilities.
• Familiarity with deployment automation tooling, platform SDKs, data modeling SDKs, and developer tooling.
• Experience with reusable enterprise data products, APIs, and platform services.
• Experience in healthcare, life sciences, medical technology, or another regulated industry.