Senior Business Intelligence Analyst

We are seeking a Senior Business Intelligence Analyst to turn business knowledge into clear, testable, and scalable data and AI rules. This person will work directly with leaders and subject-matter experts to define metrics, classifications, workflows, and decision logic; map those definitions to the correct systems, fields, filters, and historical context; and create implementation-ready requirements for Snowflake semantic models, analytics, AI agents, and automated workflows. This role is the bridge between business intent and technical delivery, not a data engineering position, and is accountable for ensuring automated outputs are accurate, explainable, governed, and ready for business use.

An A-Player in this role is relentlessly curious and precise. You ask, “What exactly do we mean by that?” and keep digging until an informal business concept becomes a rule that leaders, analysts, engineers, and AI systems can apply consistently. You identify edge cases before they become reporting conflicts, document decisions clearly, and validate automated results against real examples. You understand that trustworthy AI begins with trustworthy definitions, representative evidence, and accountable human review. At Supra Human, top performers embody our values through their actions. They take extreme ownership of outcomes, communicate with clarity, move with urgency, and always play to win.

Business Rule Discovery & Ownership

• Lead discovery sessions with business leaders and subject-matter experts to uncover definitions, decision criteria, exceptions, and the real operating process behind requested metrics or AI capabilities
• Document each rule in plain English, including its business purpose, formula or classification logic, source systems, fields, filters, grain, time treatment, inclusions, exclusions, precedence, and known edge cases
• Identify conflicting definitions, missing data, unreliable fields, duplicate logic, and source-of-truth disagreements across departments, reports, and systems
• Establish a business owner and approver for each governed rule, and clearly separate confirmed requirements from assumptions, recommendations, and items requiring owner review
• Maintain a searchable, versioned catalog connecting each business definition to its source data, implementation, test evidence, downstream consumers, and approval status

Rule Translation & AI Design

• Translate approved definitions into implementation-ready specifications for SQL models, semantic models, verified queries, dashboards, prompts, agents, classifications, and automated workflows
• Determine which decisions require deterministic logic and which are appropriate for AI-assisted interpretation, scoring, or classification
• Design AI rules with explicit input requirements, supporting evidence, confidence thresholds, fallback behavior, escalation paths, and human-review requirements
• Convert qualitative business concepts into clear rubrics, categories, examples, and evaluation criteria that can be implemented and tested consistently

Validation, Governance & Monitoring

• Build representative test cases and human-reviewed reference datasets covering expected results, edge cases, ambiguous inputs, and known failure modes
• Validate implemented rules and AI outputs against manual calculations, known examples, historical reports, and authoritative source records before release
• Monitor production rules for data drift, recurring exceptions, declining human agreement, stale definitions, and unexpected business impact
• Maintain version history, change control, approvals, and impact documentation so governed behavior changes only after explicit review and acceptance

Collaboration & Delivery

• Partner with data, engineering, product, revenue, marketing, fulfillment, and operations teams from discovery through implementation and validation
• Turn open questions into bounded research and decision requests, with clear owners, dependencies, evidence needs, and acceptance criteria
• Support self-service analytics by ensuring business questions route to approved definitions, governed queries, and the appropriate structured or unstructured source
• Provide an independent readiness recommendation before new metrics, classifications, prompts, or agent behaviors are treated as trusted business logic

• 5+ years of experience in senior business analysis, business intelligence, analytics, operations analysis, or a comparable requirements-focused role
• Strong SQL literacy and the ability to map business definitions to tables, fields, joins, filters, event timing, and historical data
• Demonstrated experience defining KPIs, calculation logic, source-of-truth rules, data contracts, test cases, and acceptance criteria
• Practical experience designing, evaluating, or governing LLM prompts, AI classifications, semantic models, agents, or human-in-the-loop workflows
• Ability to facilitate decisions among technical and non-technical stakeholders, challenge ambiguous requirements constructively, and document outcomes precisely
• Strong judgment around data privacy, least-privilege access, explainability, change control, and the responsible use of sensitive customer or business data

Nice to have:

• Experience with Snowflake, Cortex Analyst or Agents, semantic models, Sigma, HubSpot, or comparable data and analytics platforms
• Experience with Python or light scripting, historical data modeling, event-based analytics, or slowly changing dimensions
• Experience supporting revenue, marketing, sales, fulfillment, customer experience, health, fitness, or coaching analytics