Digital Data Architect

SkechersManhattan Beach, CA
1d$150,000 - $200,000

About The Position

Skechers Digital Team is seeking a Digital Data 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.

Requirements

  • Computer Science, Data Engineering, or related degree or equivalent experience.
  • 12+ years experience architecting enterprise data platforms in cloud environments.
  • 9+ 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.
  • Must hold at least one of the following Salesforce Certifications (Platform App Builder, Platform Developer 1, JavaScript Developer 1).

Nice To Haves

  • Experience with Databricks or similar distributed data/ML platforms preferred.

Responsibilities

  • 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.
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