Senior Level AI Data Analyst Jobs
Senior level ai data analyst jobs place experienced professionals in charge of analytical strategy, model governance, and the cross-functional teams that translate data into decisions. Roles concentrate across Technology & Software, Banking & Financial Services, and Healthcare & Medical Services, with 33% remote or hybrid availability, and employers like Mars, Minio, and phData hiring at this level now.
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Showing 5 of 14+ Senior Level AI Data Analyst jobs
Lead AI Solutions Architect / Engineer (Microsoft AI & Copilot)
Location: Remote (U.S.)
Employment Type: Full-Time / Contract (W2 Only)
About the Role
We are seeking an experienced Lead AI Solutions Architect / Engineer with deep expertise in the Microsoft AI ecosystem to lead the design, development, and deployment of enterprise-grade AI solutions. This role will focus on building intelligent copilots, AI assistants, and agentic AI solutions using Azure AI Foundry, Copilot Studio, Azure OpenAI, and Microsoft 365. The ideal candidate has successfully delivered enterprise AI solutions into production and understands how to build secure, scalable, and governed AI applications that integrate seamlessly with Microsoft technologies and enterprise data platforms.
Responsibilities
- Design, develop, and deploy enterprise AI solutions using Azure AI Foundry, Copilot Studio, Azure OpenAI, and Microsoft 365.
- Build AI assistants and copilots capable of securely retrieving information from enterprise knowledge bases, SharePoint, Microsoft 365, and internal documentation.
- Design multi-agent AI architectures using Azure AI Foundry Agents, Copilot Studio, Power Automate, Logic Apps, and enterprise APIs.
- Develop Retrieval-Augmented Generation (RAG) solutions including:
- Semantic Search
- Chunking Strategies
- Vector Indexing
- Prompt Engineering
- Grounding
- Evaluation Frameworks
- Integrate AI applications with Microsoft Graph, Teams, SharePoint, Microsoft 365 services, enterprise search platforms, and business applications.
- Collaborate with business stakeholders to identify and prioritize high-value AI use cases and automation opportunities.
- Ensure enterprise AI solutions comply with security, governance, RBAC, privacy, and organizational compliance requirements.
- Work closely with Data Engineering and Analytics teams to integrate AI solutions with Snowflake and enterprise data platforms.
- Establish AI guardrails, monitoring, evaluation frameworks, governance standards, and operational best practices.
- Produce architecture documentation, technical designs, deployment standards, and implementation guides to support enterprise AI adoption.
Required Qualifications
- 8+ years of experience delivering enterprise software, cloud, analytics, automation, or AI solutions.
- Proven experience deploying at least two enterprise AI/Generative AI solutions into production with measurable business adoption.
- Hands-on experience with Azure AI Foundry (Microsoft Foundry) and/or Copilot Studio.
- Experience building AI Assistants, Microsoft Copilots, or Retrieval-Augmented Generation (RAG) applications.
- Strong experience with Azure OpenAI Service and Microsoft AI technologies.
- Experience integrating Microsoft Graph, Microsoft 365, SharePoint, enterprise search, and secure organizational content retrieval.
- Strong understanding of:
- Semantic Search
- Vector Databases
- Prompt Engineering
- AI Orchestration
- Enterprise AI Security
- Experience with Microsoft Entra ID, Authentication, Role-Based Access Control (RBAC), and enterprise identity management.
- Demonstrated experience taking AI solutions from Proof of Concept through Production deployment and operational support.
Lead AI Solutions Architect / Engineer (Microsoft AI & Copilot)
Location: Remote (U.S.)
Employment Type: Full-Time / Contract (W2 Only)
About the Role
We are seeking an experienced Lead AI Solutions Architect / Engineer with deep expertise in the Microsoft AI ecosystem to lead the design, development, and deployment of enterprise-grade AI solutions. This role will focus on building intelligent copilots, AI assistants, and agentic AI solutions using Azure AI Foundry, Copilot Studio, Azure OpenAI, and Microsoft 365. The ideal candidate has successfully delivered enterprise AI solutions into production and understands how to build secure, scalable, and governed AI applications that integrate seamlessly with Microsoft technologies and enterprise data platforms.
Responsibilities
- Design, develop, and deploy enterprise AI solutions using Azure AI Foundry, Copilot Studio, Azure OpenAI, and Microsoft 365.
- Build AI assistants and copilots capable of securely retrieving information from enterprise knowledge bases, SharePoint, Microsoft 365, and internal documentation.
- Design multi-agent AI architectures using Azure AI Foundry Agents, Copilot Studio, Power Automate, Logic Apps, and enterprise APIs.
- Develop Retrieval-Augmented Generation (RAG) solutions including:
- Semantic Search
- Chunking Strategies
- Vector Indexing
- Prompt Engineering
- Grounding
- Evaluation Frameworks
- Integrate AI applications with Microsoft Graph, Teams, SharePoint, Microsoft 365 services, enterprise search platforms, and business applications.
- Collaborate with business stakeholders to identify and prioritize high-value AI use cases and automation opportunities.
- Ensure enterprise AI solutions comply with security, governance, RBAC, privacy, and organizational compliance requirements.
- Work closely with Data Engineering and Analytics teams to integrate AI solutions with Snowflake and enterprise data platforms.
- Establish AI guardrails, monitoring, evaluation frameworks, governance standards, and operational best practices.
- Produce architecture documentation, technical designs, deployment standards, and implementation guides to support enterprise AI adoption.
Required Qualifications
- 8+ years of experience delivering enterprise software, cloud, analytics, automation, or AI solutions.
- Proven experience deploying at least two enterprise AI/Generative AI solutions into production with measurable business adoption.
- Hands-on experience with Azure AI Foundry (Microsoft Foundry) and/or Copilot Studio.
- Experience building AI Assistants, Microsoft Copilots, or Retrieval-Augmented Generation (RAG) applications.
- Strong experience with Azure OpenAI Service and Microsoft AI technologies.
- Experience integrating Microsoft Graph, Microsoft 365, SharePoint, enterprise search, and secure organizational content retrieval.
- Strong understanding of:
- Semantic Search
- Vector Databases
- Prompt Engineering
- AI Orchestration
- Enterprise AI Security
- Experience with Microsoft Entra ID, Authentication, Role-Based Access Control (RBAC), and enterprise identity management.
- Demonstrated experience taking AI solutions from Proof of Concept through Production deployment and operational support.
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Who's Hiring
Top Industries Hiring
- Technology & Software
- Banking & Financial Services
- Healthcare & Medical Services
- Fintech
- Insurance
Senior Level AI Data Analyst Jobs: Frequently Asked Questions
How do I get a senior level ai data analyst job?
Employers hiring at this level look for candidates who have owned end-to-end AI and data pipelines, not just contributed to them. Demonstrating that you have set analytical direction, made architecture decisions, and mentored junior analysts gives you a clear edge. A portfolio of measurable business outcomes tied to your models matters more at this stage than credentials alone.
Which companies hire senior level ai data analysts?
Companies hiring senior level ai data analysts right now include Mars, Minio, and phData, based on current listings on Migrate Mate as of November 2026. Hiring at this level tends to come from organizations with mature data functions that need experienced professionals to lead analytical programs rather than build them from scratch.
Are there remote senior level ai data analyst jobs?
Yes, remote and hybrid options are well represented at the senior level. About 33% of senior level ai data analyst openings are remote or hybrid as of November 2026, reflecting employer confidence in placing experienced analysts outside the office. On-site roles do still exist, particularly in sectors that handle sensitive data or require close collaboration with embedded product teams.
What makes an ai data analyst role senior level?
Senior level ai data analyst roles are defined by ownership and scope rather than task execution. You are expected to design analytical frameworks, evaluate and select modeling approaches, and present findings to executive stakeholders. Leading or mentoring a team of analysts and being accountable for the quality and business impact of AI-driven insights distinguishes senior roles from mid-level positions.
Which industries hire the most senior level ai data analysts?
Senior level ai data analyst roles concentrate in Technology & Software, Banking & Financial Services, and Healthcare & Medical Services, based on current listings on Migrate Mate as of November 2026. These sectors invest heavily at the senior level because they depend on AI-driven insight for competitive decisions, regulatory compliance, or large-scale operational optimization that requires experienced analytical leadership.