Lead-to-Order (L2O) Technical Architect

This is a remote position.

Job Title: Lead-to-Order (L2O) Technical Architect

Location: Remote

Duration: Long-term Contract

The Lead-to-Order (L2O) Technical Architect is responsible for designing and governing the end-to-end Marketing-to-Revenue technology ecosystem — from lead generation through opportunity, quote, order, and billing.
This role requires a strong understanding of marketing automation, lead lifecycle management, funnel optimization, AI-enabled automation, and revenue operations, in addition to deep technical architecture expertise. The architect ensures seamless integration across HubSpot, Microsoft Dynamics 365, CPQ, Order Management, ERP, and Billing systems to drive scalable growth, operational efficiency, and data integrity across the revenue funnel.
The ideal candidate blends marketing systems knowledge with enterprise architecture capabilities and actively leverages modern AI tools to improve system design, automation, reporting, and decision-making.

Key Responsibilities
Marketing-to-Revenue Architecture Ownership

• Own the technical architecture across the full funnel:
  Lead Generation, Lead Nurturing, MQL, SQL,  Opportunity, Quote,  Order,  Invoice
• Design scalable solutions that connect HubSpot with Microsoft Dynamics 365 and downstream systems.
  
• Define lifecycle stages, lead scoring models, and routing logic across systems.
  
• Ensure alignment between marketing, sales, and finance data models.
  
• Identify automation opportunities across the funnel using AI and advanced analytics.
  

Marketing Systems & Funnel Expertise

• Architect and optimize lead capture mechanisms (forms, landing pages, campaign integrations).
  
• Design and implement advanced lead scoring frameworks (behavioural, demographic, firmographic, predictive scoring).
  
• Enable automated lead nurturing journeys and intelligent segmentation strategies.
  
• Define marketing attribution models and performance tracking dashboards.
  
• Architect funnel reporting and conversion analytics across the lifecycle.
  
• Ensure clean handoff processes between MQLs and SQLs within HubSpot and Microsoft Dynamics 365.
  
• Apply AI-driven insights to improve targeting, personalization, and funnel conversion rates.
  

HubSpot Expertise

• Architect HubSpot Marketing Hub and Sales Hub solutions aligned with enterprise revenue architecture.
  
• Design and govern bi-directional data synchronization between HubSpot and Microsoft Dynamics 365.
  
• Define workflows, automation rules, lifecycle stages, custom objects, and reporting frameworks.
  
• Implement multi-touch attribution and campaign performance measurement.
  
• Leverage HubSpot’s AI capabilities for content optimization, predictive lead scoring, and automation enhancements.
  
• Optimize segmentation, reporting, and campaign intelligence using AI-powered insights.
  

Microsoft Dynamics 365 & Revenue Systems Architecture

• Architect solutions within Microsoft Dynamics 365 Sales / Customer Engagement.
  
• Design CPQ frameworks including pricing logic, discount governance, bundling, and approval workflows.
  
• Define order orchestration and ERP integration strategies (e.g., Dynamics 365 Finance & Operations).
  
• Ensure seamless data flow from Closed-Won opportunities into order and billing systems.
  
• Support subscription models and recurring revenue scenarios.
  
• Leverage AI capabilities within Dynamics (e.g., sales insights, forecasting intelligence, Copilot features) to improve sales effectiveness and pipeline visibility.
  

Integration, Data & AI Architecture

• Define API-first and event-driven integration strategies across HubSpot, Dynamics 365, ERP, and billing systems.
  
• Establish data governance and master data management standards across the funnel.
  
• Prevent duplication and ensure clean synchronization between marketing and CRM systems.
  
• Partner with analytics teams to enable revenue intelligence and predictive modeling.
  
• Design data models that support machine learning and AI-driven insights.
  
• Define middleware architecture (MuleSoft, Boomi, Azure Integration Services).
  
• Evaluate and incorporate modern AI tools (e.g., generative AI, copilots, workflow automation agents) to enhance system performance, documentation, solution design, and operational efficiency.
  

Governance & Standards

• Establish architecture blueprints for marketing and revenue systems.
  
• Create reusable integration patterns and automation templates.
  
• Conduct system health checks and scalability assessments.
  
• Ensure compliance with data privacy regulations (GDPR, CAN-SPAM, etc.).
  
• Mentor teams on best practices in architecture and AI-enabled productivity.
  

Required Qualifications

• 8+ years of enterprise systems architecture experience.
  
• 5+ years of experience in Lead-to-Order / Marketing-to-Revenue processes.
  
• Strong hands-on experience designing solutions in HubSpot (Marketing Hub & Sales Hub).
  
• Strong experience with Microsoft Dynamics 365 Sales / Customer Engagement.
  
• Deep understanding of:
  
• Lead generation strategies
  
• Funnel optimization
  
• Lead scoring methodologies (including predictive scoring)
  
• Lifecycle stage management
  
• Campaign automation
  
• Marketing attribution models
  
• Experience integrating HubSpot with Microsoft Dynamics 365.
  
• Expertise in API design and system integration.
  
• Working knowledge of AI tools applied to marketing automation, CRM optimization, and revenue analytics.
  
• Strong knowledge of revenue operations processes.
  

Preferred Qualifications

• HubSpot certifications (Marketing Hub, Sales Hub, CMS Hub).
  
• Microsoft Dynamics 365 certifications.
  
• Experience with Dynamics 365 Finance & Operations.
  
• Experience implementing AI-driven marketing or sales intelligence solutions.
  
• Knowledge of subscription billing and SaaS revenue models.
  
• Experience with iPaaS platforms (MuleSoft, Boomi, Azure Integration Services).
  
• TOGAF or similar architecture certification.
  
• Experience in high-growth or digital transformation environments.
  

Key Competencies

• Marketing-to-Revenue systems thinking
  
• Funnel analytics and predictive optimization
  
• AI-enabled automation and analytics
  
• Cross-functional leadership (Marketing, Sales, Finance, IT)
  
• Enterprise data architecture
  
• Technical governance
  
• Strategic scalability planning