Anchor Senior Software Engineer

The role owns the end-to-end technical architecture that powers unified customer profiles, real-time data activation, and embedded AI-driven analytics across Ford's marketing, sales, and customer experience ecosystem. 

This position provides technical leadership to architect scalable, secure, and governed data and analytics solutions, guide engineering teams through implementation, and serve as the primary technical authority for Data Cloud and Tableau Next within Ford IMG.

Architecture and Design

• Design end-to-end Salesforce Data Cloud architecture, including data streams, data model objects, identity resolution, calculated insights, segmentation, and activation targets.

• Architect embedded and standalone analytics solutions using Tableau Next (preferred), or Power BI including semantic data models, AI-powered/natural-language querying, and integration with Salesforce workflows and agents.

• Define the data architecture strategy to harmonize customer data across Data Cloud, Marketing Cloud, Sales Cloud, Service Cloud, and enterprise platforms such as GCP, Azure, and AWS.

• Establish best practices for data ingestion (batch, streaming, real-time), transformation, harmonization, and identity resolution at enterprise scale.

• Design and enforce data governance, security, and privacy frameworks including field-level security, consent management, PII masking, and compliance with GDPR/CCPA.

Technical Leadership

• Serve as the primary technical advisor and subject matter expert for Data Cloud and Tableau Next across Ford IMG IT, guiding architecture decisions and platform standards.
• Lead technical design sessions and create architecture diagrams, data-flow documentation, and solution blueprints for stakeholders and engineering teams.

• Provide hands-on guidance and code/config reviews to developers and admins implementing Data Cloud pipelines, calculated insights, and Tableau Next dashboards/data models.

• Evaluate new Salesforce releases (Data Cloud, Tableau Next, Agentforce, Einstein AI) and assess architectural impact and adoption opportunities.

• Troubleshoot complex data quality, performance, and integration issues across the Data Cloud and analytics stack.

Cross-Functional Collaboration

• Partner with product managers, business stakeholders, and data engineering teams to translate business requirements into scalable technical architecture.
• Collaborate with enterprise architecture and security teams to ensure alignment with Ford's broader IT architecture, data standards, and compliance policies.
• Guide integration architecture between Data Cloud/Tableau Next and upstream/downstream systems via APIs, MuleSoft, or other integration platforms.
• Support vendor/partner engagements, providing architectural oversight for implementation projects delivered by SIs or Salesforce partners.

• 8+ years of experience in Salesforce architecture, data architecture, or enterprise solution architecture roles.

• Proven, hands-on architectural experience with Salesforce Data Cloud — data streams, DMOs/DLOs, identity resolution, calculated insights, segmentation, and activations.

• Strong working expertise in Tableau Next, including semantic modeling, embedded analytics, and AI/natural-language-driven insights within Salesforce.

• Deep understanding of Salesforce core clouds, including Marketing Cloud, Sales Cloud, and Service Cloud, and how they integrate architecturally with Data Cloud and Tableau Next.

• Strong knowledge of data modeling, ETL/ELT pipelines, APIs, and integration patterns, including real-time, batch, and event-driven integrations.

• Solid grasp of data governance, security architecture, and privacy/compliance requirements in large enterprise environments.

• Experience architecting solutions in complex, matrixed enterprise environments; automotive or similarly regulated industries preferred.

• Excellent communication skills, with the ability to translate complex technical concepts for both technical and non-technical stakeholders.

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field (Master's preferred).