GCP Solution Architect (P-153)

Smash CR • New York, NY

4d • Hybrid

About The Position

You will bridge business intake and technical execution by designing end-to-end data platform solutions on Google Cloud Platform (GCP). This role translates product and business requirements into scalable, secure, and production-ready architectures that enable delivery teams to execute with clarity and confidence.

Requirements

• 5–7 years of experience in enterprise-scale data platform architecture.
• 2–3+ years of hands-on experience with GCP data platforms.
• Proven experience leading at least two end-to-end GCP data pipeline implementations or migrations.
• Strong understanding of GCP landing zones, IAM, networking, and security models.
• Expertise in enterprise ETL and data engineering from diverse data sources into GCP.
• Deep knowledge of data ecosystem concepts (pipelines, integration patterns, lineage, metadata, data quality, monitoring).
• Ability to architect holistically across governance, reliability, performance, scalability, and security.
• Experience working in complex enterprise or consulting environments.
• Strong communication skills to bridge technical and non-technical stakeholders.

Nice To Haves

• Experience working directly with Google Cloud or prior Google employment.
• Experience building data platforms from zero to production-ready environments.
• Multi-cloud knowledge (AWS or Azure) to translate architectural patterns.
• Domain-specific data solution experience.

Responsibilities

• Translate business and product requirements into comprehensive GCP-based technical architectures.
• Design enterprise-scale data platforms, including ingestion, transformation, storage, and analytics layers.
• Lead end-to-end data pipeline migrations into GCP environments.
• Architect landing zones, IAM structures, networking, and security models in GCP.
• Define governance frameworks including lineage, metadata, data quality, and monitoring standards.
• Design reliable, scalable, and performance-optimized data ecosystems.
• Partner with stakeholders to clarify scope, constraints, and trade-offs.
• Provide technical guidance to delivery teams for implementation readiness.
• Evaluate integration patterns and enterprise data flows across multiple systems.
• Contribute to best practices for enterprise ETL and data engineering modernization.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed