Top 10 Salesforce Architect Interview Questions in 2026

Published on January 8, 2026 | 18 min read | Architect Interview Prep

Architect interviews are a different beast entirely. I remember my first architect interview - I walked in thinking I'd crush it because I knew Salesforce inside and out. Then they asked me to design a system for a company with 50 million records, real-time integrations with five different systems, and users across three continents. I realized quickly that being a great developer doesn't automatically make you a great architect.

Here's the truth: architect interviews aren't about reciting features or writing perfect code. They're about seeing the big picture, making trade-offs, and designing systems that work at scale. The interviewers want to know if you can take messy business requirements and turn them into a coherent, scalable architecture that won't fall apart in six months.

These are the questions that keep coming up in architect interviews, with the kind of thinking that separates good architects from great ones.

What Makes Architecture Questions Different?

Before we dive in, let me set expectations. Architecture questions rarely have one "right" answer. Instead, they're testing:

The best answers start with clarifying questions. Don't just dive into a solution - ask about users, data volumes, integrations, and constraints.

The Critical Questions

1. Design a solution for a company with 50 million Account records. How would you handle data storage, sharing, and performance?

This is the classic "big data" question. They're testing whether you understand Salesforce limits and when to architect around them.

My approach - start with questions:

  • How many records are actively used? (50M total doesn't mean all are accessed regularly)
  • What's the data growth rate?
  • How many users need access?
  • What are the reporting requirements?
  • Are there regulatory requirements for data retention?

The architecture I'd propose:

┌─────────────────────────────────────────────────┐
│         Active Accounts (Salesforce)            │
│     Recent/High-Value: ~5-10M records           │
│     - Fast access                                │
│     - Full sharing rules                         │
│     - Real-time reporting                        │
└──────────────────┬──────────────────────────────┘
                   │
                   │ Archive older records
                   ▼
┌─────────────────────────────────────────────────┐
│      Archive Storage (Big Objects/Heroku)       │
│    Historical/Inactive: ~40-45M records         │
│     - Lower cost storage                         │
│     - Accessible via APIs                        │
│     - Batch reporting only                       │
└──────────────────┬──────────────────────────────┘
                   │
                   │ Compliance backups
                   ▼
┌─────────────────────────────────────────────────┐
│         Cold Storage (AWS S3/Archive)           │
│     Long-term retention for compliance          │
└─────────────────────────────────────────────────┘

Key architectural decisions:

  • Data Tiering: Keep only active/recent data in Salesforce. Archive old records to Big Objects or external storage.
  • Sharing Strategy: Use Private OWD with sharing rules for active data. Archived data doesn't need complex sharing.
  • Skinny Tables: Create skinny tables for frequently accessed fields to improve performance.
  • Indexes: Custom indexes on frequently queried fields (but be careful - too many indexes slow down writes).
  • Data Archival Process: Automated batch job that moves records older than X months to archive storage.

Performance considerations:

  • Implement pagination for list views - never show all records
  • Use SOQL query optimization with selective filters
  • Consider sharding strategy if using external database
  • Implement caching layer for frequently accessed data

"I worked on a project exactly like this. We kept 3 years of data in Salesforce (about 8M records) and archived everything older to AWS S3 via Heroku Connect. Users could still search archived data through a custom Lightning component that hit our Heroku API. Saved the company about $200K annually in storage costs."

⚠️ Gotcha: Don't just say "use Big Objects." Explain when and why. Big Objects have limitations - no UI, no triggers, no sharing rules. They're great for append-only data but not for everything.
2. How would you design a real-time integration between Salesforce and an external ERP system where order data needs to sync bidirectionally?

Integration questions are huge in architect interviews. This tests whether you understand the full integration landscape, not just "make an API call."

Questions I'd ask first:

  • What's the data volume? (Orders per day/hour)
  • How "real-time" is real-time? (Seconds? Minutes?)
  • What happens if one system is down?
  • Do we need to preserve order of operations?
  • What's the network reliability between systems?

Architecture options and trade-offs:

Pattern When to Use Pros Cons
Platform Events Near real-time, fire-and-forget Native, scalable, decoupled 24-hour retention, no guaranteed delivery order
Change Data Capture Need to track all changes Automatic, captures all field changes Limited filtering, all-or-nothing per object
Outbound Messages Simple, guaranteed delivery needed Built-in retry, no code 24-hour timeout, limited throughput
Middleware (MuleSoft) Complex transformation, multiple systems Enterprise features, monitoring, error handling Additional cost and complexity

My recommended architecture:

Salesforce                    Middleware               ERP
─────────────────────────────────────────────────────────
Order Created/Updated
    │
    │ Platform Event Published
    ▼
[Order Event]───────────────►[MuleSoft]
                               │  • Transform data
                               │  • Apply business rules
                               │  • Log transaction
                               │  • Error handling
                               │
                               ▼
                         [ERP API Call]
                               │
                               ├─Success─►Update Order Status
                               │           in Salesforce
                               │
                               └─Failure─►Queue for Retry
                                          Alert support team
                                          
◄───────────────────────────────────────────────────────
ERP Order Update              
    │
    │ Webhook/Polling
    ▼
[MuleSoft Listener]
    │  • Validate payload
    │  • Transform to Salesforce format
    │  • Dedupe check
    ▼
[Salesforce REST API]
    │
    └─Updates Order

Critical design elements:

  • Idempotency: Use external IDs to ensure duplicate messages don't create duplicate orders
  • Error Handling: Dead letter queue for failed messages, alerts for support team
  • Retry Logic: Exponential backoff, maximum retry attempts
  • Monitoring: Dashboard showing sync status, errors, latency
  • Circuit Breaker: If one system is down, queue messages rather than failing

"Here's something I learned the hard way: always implement a reconciliation process. Even with perfect real-time sync, things get out of sync. We ran a nightly batch job that compared order statuses between systems and flagged discrepancies. Caught issues that would have otherwise gone unnoticed for weeks."

✓ Pro Tip: Always design for failure. Networks go down, APIs timeout, systems restart. Your architecture needs to handle these gracefully, not just when everything works perfectly.
3. Design a multi-org strategy for a global company with different business units. When would you use multiple orgs versus one org?

This question tests strategic thinking. The answer isn't always "use one org" even though that's often the default recommendation.

Single Org vs Multiple Orgs - The Trade-offs:

When ONE org makes sense:

  • Business units share customers (same accounts, contacts)
  • Need unified reporting across the organization
  • Common business processes and data model
  • Centralized IT team managing Salesforce
  • Want to maximize automation and integration efficiency

When MULTIPLE orgs make sense:

  • Fundamentally different business models (B2B vs B2C)
  • Different compliance/regulatory requirements (different countries)
  • Acquired companies with established Salesforce orgs
  • Need complete data isolation for security/privacy
  • Different fiscal calendars or business processes

A real-world example I designed:

Global manufacturing company with three divisions:

┌─────────────────────────────────────────────────┐
│           PRODUCTION DIVISION ORG               │
│    • B2B Sales                                  │
│    • Long sales cycles                          │
│    • Custom manufacturing quotes                │
└─────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────┐
│          CONSUMER DIVISION ORG                  │
│    • B2C E-commerce                             │
│    • High volume transactions                   │
│    • Marketing Cloud integration                │
└─────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────┐
│         SHARED SERVICES (Master Data)           │
│    • Master Account/Contact data                │
│    • Product catalog                            │
│    • Syncs to division orgs nightly             │
└─────────────────────────────────────────────────┘

Why we chose multiple orgs:

  • Completely different sales processes (B2B vs B2C)
  • Different user populations with different needs
  • Consumer division needed Marketing Cloud (separate org anyway)
  • Easier to manage governor limits with separated data

How we connected them:

  • Master Data Management hub for accounts and products
  • Nightly sync of master data to division orgs
  • Cross-org reporting via Analytics Cloud (Tableau CRM)
  • Single Sign-On across all orgs for IT staff

"The key insight: multiple orgs isn't the problem - lack of integration is. If you have a solid MDM strategy and good integration architecture, multiple orgs can actually be cleaner than trying to force everything into one org with complex record types and page layouts."

💡 Decision Framework: If you're spending more than 20% of your time working around governor limits, sharing rules, or conflicting processes, you probably need multiple orgs. If you're just avoiding the integration work, you need one org with better design.
4. How would you design a CPQ (Configure, Price, Quote) solution for a company with complex pricing rules and product dependencies?

CPQ questions test whether you understand business processes, not just technical implementation. They want to see if you can translate business requirements into technical architecture.

First, understand the complexity:

  • How many products? Product families?
  • What makes pricing complex? (Volume discounts? Contract terms? Bundles?)
  • Are there product dependencies? (Product A requires Product B)
  • Custom approvals needed?
  • Integration with ERP for inventory/fulfillment?

Native CPQ vs Custom vs Third-Party:

Option Best For Considerations
Salesforce CPQ Standard B2B, moderate complexity Licensing cost, learning curve, good for most cases
Custom Build Unique business model, simple pricing Full control, but high maintenance, consider long-term
Third-Party (Conga, DealHub) Specific industry needs, document generation focus Additional integration point, evaluate features vs Salesforce CPQ

Architecture for a custom solution (if building from scratch):

Quote Object
    │
    ├─── Quote Line Items (products)
    │       │
    │       ├─ Product Configuration (options/features)
    │       ├─ Price Book Entry (base price)
    │       └─ Pricing Rules (discounts/adjustments)
    │
    ├─── Approval Process
    │       ├─ Discount approval (if > threshold)
    │       ├─ Legal review (if custom terms)
    │       └─ Manager approval (if > value limit)
    │
    └─── Document Generation
            ├─ PDF Quote
            ├─ Contract (if won)
            └─ Order (send to ERP)

Key architectural components:

  • Product Rules Engine: Can Product A and B be sold together? Does Product C require Product D?
  • Pricing Calculator: Volume discounts, contract term pricing, promotional pricing
  • Configuration Validator: Ensures valid product combinations before quoting
  • Approval Matrix: Dynamic approval routing based on deal size, discount level
  • Document Generation: Professional quote PDFs, e-signature integration

"I once built a CPQ for a telecom company. The pricing was insanely complex - different rates by region, volume tiers, contract length, and promotional periods. We used a custom pricing engine with a rules table that could be updated by admins without code changes. The key was making it flexible enough for business users to maintain."

⚠️ Common Mistake: Don't underestimate document generation. Sales teams will spend hours tweaking Word templates if you don't nail this. Invest in good template design and make it easy for them to customize without breaking things.
5. Design a security model for a financial services company handling sensitive customer data with strict compliance requirements.

Security architecture questions reveal whether you understand defense-in-depth and compliance requirements. One wrong answer here could cost you the job in regulated industries.

Start with compliance requirements:

  • What regulations apply? (GDPR, SOC 2, FINRA, PCI-DSS?)
  • Data residency requirements?
  • Who can see what data?
  • Audit trail requirements?
  • Data retention and deletion policies?

Multi-layered security architecture:

Layer 1: Organization Level

  • Shield Platform Encryption: Encrypt sensitive fields at rest (SSN, account numbers)
  • Event Monitoring: Track all data access, exports, API calls
  • Login IP Restrictions: Limit access to corporate networks or VPN
  • Session Settings: Timeout after 15 minutes of inactivity

Layer 2: Object and Field Level

  • OWD: Private for all sensitive objects
  • Field-Level Security: Restrict sensitive fields (SSN) to compliance roles only
  • Record Types: Different views based on user role

Layer 3: Record Access

  • Role Hierarchy: Aligned with organizational structure
  • Sharing Rules: Minimal use, well-documented
  • Manual Sharing: Disabled or heavily logged
  • Criteria-Based Sharing: For specific use cases (account team, region)

Layer 4: Application Level

  • Custom Apex: Always with sharing keyword