Position Summary: We are seeking an exceptionally experienced and innovative Salesforce Data Cloud Senior Architect.
This individual will be a key leader within our Salesforce practice, driving strategic growth by leveraging Salesforce Data Cloud 360 and Agentforce. You will collaborate closely with clients to build highly differentiated, scalable solutions, providing unique insights into data engineering, segmentation, and activation. We are looking for a visionary with a proven track record in end-to-end production deployments and the leadership skills to mentor teams and influence client stakeholders.
Key Responsibilities:
Strategic Leadership & Agentforce Growth:
- Champion Data Cloud 360 & Agentforce: Lead the charge in positioning Salesforce Data Cloud 360 and Agentforce as core drivers of client growth and digital transformation.
- Build Differentiated Solutions: Architect and design cutting-edge, innovative Data Cloud solutions that go beyond standard implementations, creating significant competitive advantages for clients.
- Develop Solution Options: Act as a trusted advisor, presenting unique, well-reasoned solution options to complex client challenges in Data Engineering, Segmentation, and Activation, considering business objectives, technical constraints, and cost implications.
- Influence Client Strategy: Engage with C-level stakeholders to articulate the business value of Data Cloud, influence their technology roadmap, and foster long-term strategic partnerships.
- Drive Business Development: Actively participate in pre-sales activities, leading solution discovery, proposal development, and client presentations.
Advanced Solution Architecture & Engineering:
- Complex Architectural Design: Design distributed, resilient, and performant enterprise-grade Data Cloud architectures that support both batch and real-time streaming data strategies. Define logical, physical, and conceptual data models based on the Cloud Information Model (CIM).
- High-Scale Ingestion & Data Engineering:
- Implement Change Data Capture (CDC) mechanisms and optimized batch ingestion strategies (leveraging the Ingestion API) to ensure minimal latency for critical business metrics.
- Utilize advanced Salesforce Data Pipelines or native Data Cloud transformation tools for complex data preparation, cleansing, and validation at scale.
- Design robust data-quality control frameworks (e.g., data lineage tracking, schema evolution management).
- Define architectures involving Bring Your Own Data (BYOD) via storage connectors (AWS S3, Azure Blob, GCS) or direct data federation where performance is critical.
- Identity Resolution & Unified Profile Architecture:
- Architect sophisticated identity resolution rule sets.
- Analyze data complexity and profile quality to define optimal matching and reconciliation rules (e.g., precise, fuzzy, prioritizations).
- Design frameworks for managing identity across multiple orgs (C360/Data Cloud 1 or Data Cloud 2 models) and hybrid environments.
- Optimize profile definition and storage management to prevent profile bloat while maximizing the usefulness of unified profiles.
- Segmentation & Activation Optimization:
- Analyze business segmentation needs and design efficient segmentation strategies, prioritizing performance and avoiding query complexity.
- Design sophisticated multi-channel activation paths across Salesforce clouds (Sales, Service, Marketing, Commerce) and non-Salesforce endpoints (external APIs, ad-tech platforms).
- Optimize activation frequency, throughput, and error handling for complex, near-real-time activation requirements.
- Advanced Platform Integration (Agentforce/Einstein):
- Directly embed Agentforce and Einstein capabilities within the architecture by defining how Data Cloud insights fuel predictive AI and recommendation engines.
- Specify integration patterns using Platform Events, Kafka, or other middle-tier technologies for complex, event-driven interactions and near-real-time agent responses.
- Define how Data Cloud unified profiles are consumed by Einstein Bots and Sales/Service AI functionality.
- Security, Governance, & Compliance (at Scale):
- Architect comprehensive security models encompassing OAuth/OIDC, IAM roles for federated access, and fine-grained data-access controls within Data Cloud (Data Spaces, permission sets).
- Design scalable data retention and archiving policies that balance operational needs with regulatory compliance.
- Develop rigorous monitoring, logging, and alerting strategies for all components of the Data Cloud architecture.
- Ensure all architectural components comply with relevant data privacy regulations (GDPR, CCPA, HIPAA, as applicable).
Client Delivery & Production Management:
- Lead Production Deployments: Oversee the successful execution of multiple end-to-end Data Cloud production deployments, ensuring adherence to quality standards and project timelines.
- Manage Client Projects: Provide technical leadership and guidance throughout the project lifecycle, managing client expectations, and ensuring successful delivery.
- Document and Communicate Solutions: Create clear and comprehensive architectural documentation, solution diagrams, and technical specifications for stakeholders and delivery teams.
- Ensure Solution Adoption: Work closely with clients to ensure effective user adoption and realization of business value.
Qualifications:
- Years of Experience: Minimum of 15 years of progressive experience in technology consulting, architecture, or related roles.
- Client-Facing Prowess: Minimum of 10 years of successful client-facing experience, with a proven ability to interact confidently with C-level executives.
- Data Cloud Expertise: Hands-on experience architecting and implementing Salesforce Data Cloud solutions (formerly CDP/Customer 360 Audiences) is essential. Deep knowledge of the platform's capabilities and limitations.
- Agentforce Knowledge: In-depth understanding of the Agentforce vision and its potential to enhance Data Cloud solutions.
