About Banyan GroupBanyan Group is an independent, global hospitality company with a portfolio spanning 90+ hotels and resorts, 140+ spas, and 20+ branded residences across 22 countries and 12 brands. Our flagship experiential membership programme, with Banyan, unifies guests across the entire portfolio through milestone- and challenge-based recognition rather than a conventional points scheme.
We are mid-way through a major transformation of our CRM, loyalty, and guest engagement technology — built on Salesforce (Marketing, Data, Loyalty, and Service Cloud) and MuleSoft, integrated with hotel PMS systems, booking engines, and a range of hospitality platforms across 100 properties globally.
The Role
We are building internal architecture and governance capability so that Banyan Group can own and evolve its technology platform independently — not remain dependent on any single vendor or implementation partner.
This role sits inside our Digital & Technology team. You will serve as the internal design authority for our CRM and integration landscape: reviewing and challenging technical decisions, ensuring our architecture remains sound, scalable, and secure, and guiding both internal staff and external delivery partners.
Working with AI as a Force Multiplier
We expect this role to make active, strategic use of AI tools — Claude in most regions, an equivalent in China — as a core part of how work gets done. This is not optional and not peripheral.
What this means in practice:
- Using AI to generate solution design options, integration patterns, and configuration drafts — then applying your domain judgment to validate, challenge, and improve what is produced
- Prompting AI to write DataWeave transformations, Apex code, or MuleSoft flows as a starting point — then reviewing and refining with the expertise to know when the output is wrong
- Accelerating documentation: architecture diagrams, decision records, integration specs, runbooks
- Using AI to research platform capabilities, compare design options, or stress-test a proposed approach against edge cases
- Staying ahead of what AI can and cannot do reliably — and calibrating how much to trust its output in each context
You do not need to be the deepest Salesforce or MuleSoft expert in every room. You need to be technically strong enough to validate what AI and external partners produce, and to intervene decisively when something is wrong.
What You Will Do
Architecture & Technical Design Authority
- Own the architectural vision for Banyan Group's CRM and integration landscape — current state (Salesforce + MuleSoft) and future state
- Lead technical design sessions with internal teams and external delivery partners; produce and maintain architecture diagrams, data flow documentation, and decision records
- Act as design authority and gatekeeper: review and approve (or challenge) solution blueprints from external vendors before implementation proceeds
- Define scalable data models, integration patterns, and API contracts aligned to enterprise standards and long-term platform flexibility
- Identify technical debt, anti-patterns, and architectural shortcuts early — and recommend remediation paths
Integration & Data Architecture
- Govern the integration landscape between Salesforce and hotel PMS systems (Opera Cloud, Opera On-Premise, Opera 5), booking engines, spa and F&B platforms, and third-party vendors
- Ensure integration patterns remain consistent, auditable, and maintainable — with MuleSoft as the current hub but without assuming it is permanent
- Define identity resolution, data quality, and deduplication standards across the guest profile ecosystem
- Oversee data flow design for real-time and batch processing, ensuring consistency between CRM, Data Cloud, and downstream marketing and operations systems
Vendor Oversight & Delivery Governance
- Independently review and challenge technical deliverables from external implementation partners — you must be capable of identifying gaps without depending on the partner to self-report
- Establish and maintain internal runbooks for hotel onboarding, PMS integration, and platform configuration — progressively reducing Banyan's dependency on external vendors
- Define test case standards and UAT expectations; ensure testing covers not just functional requirements but integration reliability, data integrity, and security controls
- Participate in architecture review boards and steer discussions toward outcomes that serve Banyan's long-term interests, not vendor preferences
Security, Compliance & Governance
- Collaborate with the Corporate IT and Cybersecurity team to ensure the platform meets security standards, including VAPT remediation, access controls, and data residency requirements
- Ensure compliance with GDPR, PDPA, PIPL (for China operations), and internal data governance policies
- Define and enforce least-privilege access models across Salesforce roles and MuleSoft credentials
- Flag and escalate compliance risks proactively — particularly around guest PII, cross-border data flows, and AI connector usage
Platform Operations (Selective)
- Provide hands-on support for complex platform issues where architecture judgment is needed — not routine administration
- Support environment management, release planning, and deployment governance in collaboration with the external delivery partner
- Oversee data quality monitoring and coordinate remediation when integration failures or data integrity issues affect live operations
Hands-On Platform Evolution
You are expected to build, not just govern. Using AI as a force multiplier, you will own and deliver bounded platform changes end-to-end:
- Scope, design, and implement well-defined platform changes: retiring unused data streams, adjusting identity resolution rules, modifying integration mappings, updating Loyalty Cloud tier logic, reconfiguring Marketing Cloud journeys or suppression lists
- Apply SDLC discipline to your own changes: sandbox-first development, review of AI-generated code or configuration, regression testing, documented deployment, and a rollback plan
- Distinguish clearly between what you can deliver independently, what needs external delivery support, and what requires a full architecture review before any work begins
- Produce your own test cases and verify your own changes before release — not dependent on a separate QA function for routine platform evolution
- Use AI tools (Claude or equivalent) to generate DataWeave transformations, Apex code, Flow logic, or configuration scripts — then review and validate with the technical depth to catch errors before they reach production
A practical example: if Banyan decides to stop managing transactional email sends from Loyalty Cloud and to deprovision non-member records from both CRM and Data Cloud, you would scope the impact, design the change safely, execute it across Salesforce and MuleSoft, test it end-to-end, and document what changed — with AI assistance throughout, but under your own judgment and ownership.
What We Are Looking For
Foundation (Required)
- A background in software engineering, enterprise integration, or data architecture — Salesforce and MuleSoft came later in your career, not first
- 7+ years of hands-on experience in integration architecture, enterprise application architecture, or equivalent — you have built things, debugged production failures, and owned technical decisions under pressure
- Solid understanding of integration design patterns: event-driven architecture, API-first design, pub/sub, synchronous vs asynchronous flows, idempotency, error handling at scale
- Proficiency in at least one general-purpose programming or scripting language; comfortable reading and evaluating code across languages you did not write yourself
- Grounded understanding of data modelling, identity resolution, and the realities of data quality at enterprise scale (duplicate records, incomplete profiles, schema migrations)
- Ability to produce clear technical documentation — architecture diagrams, data flow specs, decision records — that non-specialists can also follow
Salesforce & MuleSoft (Hands-On Working Knowledge Required)
- Enough depth in Salesforce (Marketing Cloud, Data Cloud, Loyalty Cloud, Service Cloud) to make real configuration and logic changes independently — not just review them
- Able to sit down with AI assistance and evolve the platform in a controlled way: modifying data streams, adjusting flows, updating integration mappings, retiring unused components, or reconfiguring journey logic
- Working knowledge of MuleSoft / CloudHub 2.0 — integration flows, DataWeave, connector configuration, error handling, and monitoring — sufficient to write, debug, and deploy changes with AI support
- Understanding of Salesforce multi-tenant constraints, governor limits, and security model — enough to catch bad practices early and design safely
- Familiarity with Salesforce APIs (REST, SOAP, Bulk, Streaming) and how they are used in large-scale PMS and third-party integrations
- Understanding of SDLC as it applies to a configuration-heavy platform: sandbox management, change sets or CI/CD deployment, regression testing, and change documentation
Domain Experience (Advantageous)
- Hospitality, travel, retail, or loyalty-driven industries — particularly guest 360, membership ecosystems, or omnichannel personalisation
- Experience with hotel PMS systems (Opera Cloud or On-Premise) — even at the integration interface level — is genuinely valuable given our current programme
- Prior experience overseeing or governing an external implementation partner, not just working alongside one
- Multi-jurisdiction data privacy experience — GDPR, PDPA, and ideally PIPL for China operations
AI Fluency (Required)
- Active, confident user of AI tools (Claude, GPT-4, or equivalent) in a technical context — not for general productivity but for architecture, code review, and design work
- Capable of crafting effective prompts that produce useful technical output, and of recognising when AI output is incorrect, incomplete, or subtly wrong
- Comfortable working in a context where AI tools are part of the daily workflow, not an occasional novelty
- Awareness of AI governance considerations — what data should and should not be sent to external AI services, and how to operate responsibly in a regulated, guest-data environment
Who we are looking for
An architect by formation — someone whose foundation is software engineering, enterprise integration, or data systems — who has since mastered Salesforce and MuleSoft as tools in service of a broader craft. We are explicitly not looking for someone whose entire career has been built on the Salesforce platform.
The immediate technology context is Salesforce and MuleSoft. But the architecture decisions made today must remain defensible if those platforms change tomorrow. For example, our E-commerce domain is making use of Kong as an API gateway for integration. We need someone who thinks in domain terms first — loyalty mechanics, integration patterns, data governance, guest identity — and platform terms second.
What we deliberately do not require
- Salesforce certifications — domain depth and independent judgment matter more than credential accumulation
- Full-stack MuleSoft or Apex development capability — you will use AI to generate and iterate on implementation, with your own judgment applied to validate and own the result
- A background that is 100% Salesforce — in fact, we actively prefer candidates who can evaluate Salesforce critically because they know alternatives
- Experience with every integration in our current stack — curiosity and architecture first principles transfer across systems
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