Salesforce Data Cloud Architect
Role details
Job location
Tech stack
Job description
Skechers Digital Team is seeking a Salesforce Data Cloud Architect reporting to the Director, Digital Architecture, Consumer Domain. This role is responsible for designing and governing Skechers' Consumer Data 360 ecosystem, enabling identity resolution, high-quality data foundations, personalization, loyalty intelligence, and machine learning capabilities across digital and retail channels.
The ideal candidate will be a strong technical leader, have hands-on full-stack technical knowledge in enterprise technologies related to Skecher's consumer domain, and have the ability to work in a fast-paced agile environment. You should have knowledge of consumer programs from an architecture/industry perspective, and you should have strong hands-on experience designing solutions on the Salesforce Core Platform (including configuration, integration, and data model best practices).
You will work cross-functionally with Digital Engineering, Data Engineering, Data Science, Loyalty, and Marketing teams to architect scalable, secure, and high-performance data platforms that support advanced personalization and recommender systems.
WHAT YOU'LL DO:
- Responsible for the full technical life cycle of consumer platform capabilities which includes:
- Capability roadmap and technical architecture in alignment to consumer experience
- Technical planning, design, and execution
- Operations, analytics/reporting, and adoption
- Define and evolve Skechers' Consumer Data 360 architecture, including identity resolution (deterministic and probabilistic matching) and unified customer profiles.
- Architect scalable data models and pipelines across CDP, CRM, e-commerce, marketing automation, data lake, and warehouse platforms.
- Establish enterprise data quality frameworks including validation, deduplication, anomaly detection, and observability.
- Optimize SQL workloads and large-scale distributed queries through performance tuning, partitioning, indexing, and workload management strategies.
- Design and oversee ML pipelines supporting personalization, churn modeling, and recommender systems.
- Partner with Data Science teams to productionize models using distributed platforms such as Databricks (Spark, Delta Lake, MLflow preferred).
- Ensure secure data governance, access control (RBAC/ABAC), and compliance with GDPR, CCPA, and related privacy regulations.
- Provide architectural oversight ensuring performance, scalability, resilience, and maintainability.
- Collaborate with stakeholders to translate business objectives (LTV growth, personalization lift, engagement) into scalable data solutions.
Requirements
- Computer Science, Data Engineering, or related degree or equivalent experience.
- 10+ years experience architecting enterprise data platforms in cloud environments.
- 8+ years experience with data engineering with a focus on consumer data.
- 6+ years experience working with Salesforce platforms, including data models and enterprise integrations.
- Strong experience with Data 360 and identity resolution architectures.
- Proven expertise in SQL performance tuning and large-scale data modeling.
- Hands-on experience implementing ML pipelines and recommender systems in production environments.
- Experience with cloud technologies (AWS, GCP, or Azure).
- Experience with integration patterns (API, ETL, event streaming).
- Experience providing technical leadership and guidance across multiple projects and development teams.
- Experience translating business requirements into detailed technical specifications and working with development teams through implementation, including issue resolution and stakeholder communication.
- Strong project management skills including scope assessment, estimation, and clear technical communication with both business users and technical teams.
- Salesforce Certifications preferred (Platform App Builder, Platform Developer 1, JavaScript Developer 1).
- Experience with Databricks or similar distributed data/ML platforms preferred.
Benefits & conditions
The pay range for this role is $150,000 - $200,000/yr USD.