Senior Data Platform Architect (Contract) Google Cloud Platform - W2 & Remote

• Lead rapid POCs and technical exploration to validate EDP and Enterprise Consumption Layer patterns (data modeling approach, performance/cost, security, operability).
• Define and evolve architecture patterns and reference implementations for:
• Building and maintaining the Enterprise Consumption Layer (enterprise-ready star schemas / dimensional models)
• Data product structure, onboarding standards, and lifecycle (naming, documentation, quality expectations)
• BI and downstream access patterns (including guardrails for scalable consumption)
• Build hands-on prototypes on Google Cloud Platform when needed (you can implement, not just design).
• Partner with architects, engineers, and product owners to design solutions that balance:
• Speed vs durability
• Innovation vs standardization
• Incremental delivery vs long-term platform fit
• Contribute to practical enablement of data/AI agent use cases where valuable (e.g., data discovery, metadata-driven workflows, quality checks, operational insights).
• Provide technical leadership through design reviews, tradeoff decisions, documentation, and stakeholder communication.
• Operate in a Kanban/Agile model using Jira, delivering measurable outcomes iteratively.

• 8+ years overall IT experience with significant hands-on delivery in modern data platforms.
• Strong experience building on Google Cloud Platform, including several of:
• BigQuery (modeling, optimization, cost/performance patterns)
• Dataform (or equivalent transformation framework)
• GCS, Cloud Composer, Cloud Functions/Cloud Run, IAM
• Logging/monitoring patterns (Cloud Logging/Monitoring)
• Demonstrated ability to work across architecture + implementation: define a pattern, prototype it, and guide adoption.
• Strong foundation in:
• Dimensional modeling / star schemas, metric definitions, and consumption-ready data structures
• Data quality mindset (what enterprise-ready looks like)
• Security and access design (least privilege, domain/dataset-based access concepts)
• Strong communication skills with the ability to explain tradeoffs to both technical and non-technical stakeholders.

• Experience in retail / consumer / omni-channel domains (customer, product, inventory, orders, pricing, promotions, loyalty).
• Familiarity with semantic layer concepts (even if not implementing one).
• Experience with data catalog / metadata platforms and governance workflows.
• Exposure to LLM-enabled/agentic tooling and automation patterns.
• Prior work in platform modernization or EDW migration programs.
• Experience defining enterprise standards (naming, dataset organization, data product onboarding, testing patterns).

• Collaborative, outcome-driven, and comfortable with ambiguity and early-stage exploration.
• Bias toward action: prototype fast, document clearly, scale what works.
• Strong ownership: identifies gaps, proposes options, drives alignment and closure.

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