Business Analytics Architect, Muck Rack

• We’re looking for a collaborative, self-motivated Analytics Architect to join our Business Data Analytics team
• 7+ years of experience designing and evolving modern data and analytics architectures, including responsibility for architectural decisions that span multiple systems, teams, or business use cases
• Deep experience with modern cloud data platforms and analytics engineering practices, including Snowflake, Databricks, dbt, Python, and SQL
• Experience designing scalable data models, transformation pipelines, semantic or metrics layers, and integration patterns that enable trusted self-service analytics
• Experience architecting or implementing AI-enabled data systems, such as natural language analytics, AI agents, Retrieval-Augmented Generation (RAG), vector search, or related LLM-powered data workflows
• Strong knowledge of enterprise data governance, security, privacy, access control, and data quality practices, with experience translating those requirements into practical technical architecture
• Experience establishing engineering practices such as automated testing, CI/CD, observability, version control, and reliable deployment patterns for data and analytics systems
• Demonstrated ability to set technical direction, evaluate complex architectural trade-offs, and influence decisions across teams without relying on direct authority
• Strong communication skills with the ability to translate complex data and AI architecture into clear decisions, standards, and technical direction for both technical and business partners
• Approach architecture pragmatically, balancing immediate business needs with scalability, maintainability, security, and long-term platform health
• Build alignment across technical and non-technical teams and communicate architectural decisions and trade-offs clearly
• Take ownership of ambiguous, complex problems and create clarity and actionable technical direction
• Look for opportunities to create reusable systems, standards, and patterns that increase the effectiveness of other teams
• Share knowledge generously and mentor teammates through complex technical and architectural challenges
• Proactively incorporate AI tools into day-to-day work to improve productivity and accelerate delivery

Desirable

• Reporting to the VP, Analytics, you’ll serve as the lead architect for Business Data Analytics, defining and driving an AI-first data and analytics architecture that modernizes our analytics platform and enables new ways for teams to access and interact with data
• You’ll establish the technical blueprint for a modern data analytics stack supporting Data Ingestion to Snowflake / Databricks, Data Modeling / Semantic Layers (dbt, Python, SQL), Natural Language Analytics (Agents), Data Activation (rETL, System to System), and Self-Service Analytics (BI Tools)
• You’ll collaborate across Data Science, Engineering, Product, and Revenue Operations to establish scalable architecture, integration patterns, governance, and engineering practices that enable trusted data and AI-powered analyticsacross the business
• Define and drive the target architecture for an AI-first enterprise data and analytics platform, establishing the technical direction and patterns needed to modernize and consolidate the analytics technology stack
• Architect scalable data infrastructure, ingestion and transformation frameworks, storage models, and integration patterns across Snowflake, Databricks, dbt, Python, SQL, and related systems
• Design governed semantic data layers and the supporting architecture for AI agents, natural language querying, conversational analytics, and other AI-powered data experiences
• Establish architecture patterns for retrieval, APIs, and integrations that allow AI agents and applications to securely discover, understand, and interact with trusted enterprise data
• Lead the evolution of data governance, security, privacy, access control, and compliance patterns across the analytics stack, balancing accessibility with appropriate safeguards
• Establish and champion engineering standards for data modeling, testing, observability, CI/CD, documentation, deployment, and system integration, improving the reliability and maintainability of the analytics platform
• Provide technical leadership and mentorship to the Analytics Engineers on the team

• Below you'll find an outline of the interview plan for this role. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision
• 30 min interview with a member of our Talent Team
• A 1 hour zoom interview with the hiring manager
• Peer interviews with several team members
• Skills Assessment
• Executive interviews
• 30-minute Bar Raiser