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지금 많이 보는 기업

지금 많이 보는 기업

Ford
Ford

Automotive manufacturer

Salesforce Solution Architect Specialist/Senior Specialist

직무솔루션 아키텍트
경력시니어급
위치Bangkok, Thailand
근무오피스 출근
고용정규직
게시2개월 전
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필수 스킬

Go

Regional Architecture Ownership & Standardization

  • Own the regional target architecture and multi-release roadmap for Automotive Cloud (Sales).

  • Establish architecture principles/guardrails, reference patterns, and governance (e.g., declarative-first, reuse-first, integration standards, data quality rules).

  • Lead cross-market fit-gap and standardization decisions; manage trade-offs between global consistency and local requirements and regulations.

Automotive Cloud (Sales) Solution Architecture — Year 1 Scope

  • Lead Management: define capture channels, routing/assignment rules, lifecycle stages, deduplication approach, conversion governance, and auditability.

  • Opportunity Management: define opportunity lifecycle/stages, pipeline governance, required data and controls, and handoffs across sales, dealer, and back-office processes.

Price & Product Configuration:

  • Define product catalog strategy (product hierarchy, options/variants as applicable), configuration governance, and lifecycle management.

  • Define pricing architecture (price books, discounting/approvals, promotions as applicable) and controls.

  • Align product and pricing integration with SAP (and dealer/DMS where relevant), including system-of-record, synchronization, and reconciliation approach.

  • Account & Contact Management: define standard model (including dealer/customer structures), relationship patterns, stewardship responsibilities, and data quality controls.

  • Vehicle & Asset Management: define entity strategy, lifecycle/state model, and relationships to accounts/contacts/leads/opportunities; align with MDM/SAP/DMS as system of record.

  • Demand Forecast: define pipeline governance, forecast logic/inputs, operational cadence, and downstream integration/analytics needs.

  • Workflow & Approvals: design scalable approval frameworks, exception handling, audit trails, and policy controls across markets.

  • Reporting & Dashboards: define KPI governance (definitions, ownership, refresh cadence), role-based dashboard strategy, and “single source of truth” principles.

Agentforce Architecture (Responsible AI for Sales)

  • Define AI use-case portfolio and guardrails for prioritized sales scenarios (e.g., lead/account/vehicle summarization, recommended next steps, guided selling prompts, forecast explanations).

  • Define grounding strategy leveraging Data Cloud and approved enterprise sources; set requirements for accuracy, recency, and traceability.

  • Define access controls and safety requirements (least privilege, sensitive data handling, auditability).

  • Ensure Agentforce behaviors, retrieval sources, and actions respect Ford-standard consent constraints, including enforcement and auditability for consent-sensitive data.

  • Establish evaluation and monitoring framework: quality, safety, latency, drift, and business impact; define go/no-go gates for production rollouts.

Enterprise Integration & Security Architecture

  • Facilitate Mule Soft API-led standards: interface contracts, versioning, canonical mapping where appropriate, idempotency/retries, error handling, monitoring/alerting, SLAs, and support model.

  • Define integration strategy and reconciliation approach; clarify system-of-record and data stewardship for shared domains.

  • Define integration approach (security, connectivity, data quality, rollout scalability).

  • Define integration approach (as needed) between Salesforce/Data Cloud and the Ford-standard consent component, including system-of-record, synchronization rules, and operational monitoring.

Delivery Governance & Stakeholder Leadership

  • Run architecture and design reviews; manage cross-domain dependencies and risks (data, integration, security, release).

  • Partner with Product Owner(s) on backlog readiness (acceptance criteria, NFRs, testability) and release scope decisions.

  • Coach delivery teams/SI partners on standards and patterns; ensure solutions are supportable and aligned with enterprise architecture.

  • Own documentation quality (solution designs, integration/data flows, security model, NFRs, operational readiness, release notes).

  • Bachelor’s degree in relevant discipline.

  • Salesforce Certified Administrator: Salesforce Certified Sales Cloud Consultant are required

  • Automotive Cloud; Data Cloud; Mule Soft; Agentforce/Salesforce AI credential (as available) are preferred

  • 6–9+ years Salesforce delivery experience with solution architecture ownership for complex programs (multi-market and/or multi-cloud).

  • Strong experience across integration landscape: Mule Soft. Other integration landscape experience e.g. SAP, dealer/DMS ecosystems, AD/SSO, and enterprise data platforms (MDM/GCP) are preferred.

  • Strong architecture competencies: Salesforce security, data modeling, automation patterns, SDLC, DevOps/release governance, and operability.

  • Strong customer data architecture capability: identity resolution, consent/privacy, segmentation, activation, and data quality/lineage.

  • Agile delivery fluency (Jira/Confluence) and strong stakeholder leadership.

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Ford 소개

Ford

Ford

Public

The Ford Motor Company is an American multinational automobile manufacturer headquartered in Dearborn, Michigan, United States. It was founded by Henry Ford and incorporated on June 16, 1903.

10,001+

직원 수

Dearborn

본사 위치

$48B

기업 가치

리뷰

10개 리뷰

3.7

10개 리뷰

워라밸

3.8

보상

4.2

문화

3.5

커리어

3.2

경영진

2.8

68%

지인 추천률

장점

Good benefits and compensation

Work-life balance and flexibility

Supportive colleagues and positive environment

단점

Poor management and communication

Limited career advancement

High workload and stress

연봉 정보

21개 데이터

Mid/L4

Senior/L5

Mid/L4 · ADAS Data Analytics Engineer

1개 리포트

$132,847

총 연봉

기본급

$102,190

주식

-

보너스

-

$132,847

$132,847

면접 후기

후기 3개

난이도

3.0

/ 5

소요 기간

14-28주

경험

긍정 0%

보통 67%

부정 33%

면접 과정

1

Application Review

2

Phone Screening

3

Technical Interview

4

Team Interview

5

Offer

자주 나오는 질문

Technical Knowledge

Behavioral/STAR

Past Experience

Coding/Algorithm