Job Title: GenAI Architect & Analytics
Location: Minneapolis (3–4 days onsite)
Role Summary
The Analytics & GenAI Architect is responsible for designing and governing enterprise-grade, AI-enabled analytics solutions for reporting and advanced analytics. This role bridges traditional BI/reporting with GenAI-powered experiences such as conversational BI, KPI-driven Q&A, and insight generation.
This is an architecture and governance leadership role, focused on scalable, secure, and business-aligned solutions—not deep ML model training.
Key Responsibilities
1) End-to-End Architecture for AI-enabled Analytics
• Define architectures across data ingestion, modeling, semantic layers, BI, and GenAI interaction patterns
• Design conversational analytics aligned with governed KPIs and datasets
• Establish architecture guardrails for scalability, security, and performance
2) Semantic Layer, KPIs & Enterprise Metrics Strategy
• Design enterprise semantic models (metrics, dimensions, definitions)
• Ensure “single version of truth” across reporting and GenAI outputs
• Enable reusable and auditable BI semantic layers
3) GenAI Design Patterns for Analytics
• Define patterns for prompt grounding, KPI-based queries, and structured retrieval
• Implement tool/function calling (SQL, APIs, BI tools) for reliable data access
• Establish validation frameworks to reduce hallucinations and improve explainability
• Guide conversational BI and “explain my report” use cases
4) Data Readiness, Governance & Responsible AI
• Ensure data quality, lineage, metadata, and access control readiness
• Define Responsible AI guardrails (auditability, traceability, transparency)
• Align GenAI outputs with enterprise reporting standards
5) Cross-Functional Leadership
• Act as technical authority across delivery teams
• Build reusable assets (architecture blueprints, standards, frameworks)
• Support business use-case prioritization and execution strategy
Technology Landscape (Preferred)
Data Platforms:
BigQuery, Snowflake, Databricks, Synapse/Fabric, Redshift
Data Transformation & Orchestration:
dbt, Airflow, scheduling/orchestration frameworks
BI & Semantic Modeling:
Looker, Power BI, Tableau, ThoughtSpot, KPI frameworks
GenAI Platforms:
Enterprise LLM platforms (e.g., Gemini, OpenAI, etc.)
RAG, structured retrieval, conversational BI
Governance & Observability:
Data cataloging, lineage, privacy, access control
AI observability, monitoring, evaluation frameworks
Required Qualifications
• 10+ years in data/analytics/BI architecture
• Strong expertise in data modeling, KPI frameworks, semantic layers
• Experience designing enterprise-scale analytics platforms
• Hands-on experience applying GenAI in analytics (conversational BI, Q&A, insights)
• Strong stakeholder management and business-to-technical translation skills
Preferred Qualifications
• Experience in regulated industries (Healthcare / Insurance)
• Experience in multi-partner environments (client + SI + hyperscaler)
• Proven ability to define reference architectures and reusable patterns
