SMASH, Who we are?
We believe in long-lasting relationships with our talent. We invest time getting to know them and understanding what they seek as their professional next step.
We aim to find the perfect match. As agents, we pair our talent with our US clients, not only by their technical skills but as a cultural fit. Our core competency is to find the right talent fast.
This role is based in New York City, NY , with a requirement of 3 days per week onsite . You must have U.S. citizenship or a valid U.S. work permit to apply for this role.
Role summaryTranslate 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.
Requirements – Must-haves
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 (optional)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.
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