Data Solutions Architect

Data Solutions Architect

Location: Santa Clara, CA



Work Arrangement: Full-Time | On-Site



Experience: 8 10+ Years



Work Authorization: U.S. Citizens, Green Card Holders, and Green Card EAD holders only

About the Opportunity

We are seeking a highly experienced Data Solutions Architect to lead the architecture and delivery of next-generation, cloud-based data platforms. This is a hands-on architecture role focused on data warehousing, lakehouse architectures, multi-tenant platforms, enterprise data integration, governance, and advanced analytics .

The ideal candidate will have a strong track record designing scalable and secure enterprise data solutions and the ability to translate complex business requirements into practical, high-performance technical architectures.

You will work closely with engineering, security, infrastructure, and business stakeholders to define architecture strategy, establish reusable design patterns, and drive implementation of modern data platforms supporting analytics, AI/ML, and GenAI initiatives.

Key Technical & Functional Requirements 1. Architecture & Data Platform Design

• Define and implement end-to-end data platform architecture across ingestion, storage, transformation, and consumption layers.

• Design scalable cloud-native solutions using modern Lakehouse and Data Mesh architecture principles.

• Establish enterprise reference architectures, standards, and reusable design patterns.

• Translate business and technical requirements into scalable architecture roadmaps and implementation strategies.

2. Multi-Tenant Data Platform Architecture

• Architect secure, scalable, and highly available multi-tenant data environments .

• Design strong tenant-level data isolation and segregation strategies.

• Implement policy-based access control, encryption, and security mechanisms.

• Define customer onboarding, tenant provisioning, configuration, and lifecycle-management processes.

• Ensure platforms meet enterprise security, audit, privacy, and regulatory requirements.

3. Cloud Data Platform & Data Warehouse

• Lead architecture and implementation of modern cloud data warehouses and lakehouse platforms .

• Design high-throughput batch and real-time data pipelines.

• Optimize data models, workloads, query performance, storage, and processing.

• Develop architectures capable of supporting large-scale analytics and evolving business requirements.

• Drive performance, scalability, availability, and cost optimization across the data ecosystem.

4. Data Governance, Security & Compliance

• Define and implement enterprise data governance frameworks.

• Establish data cataloging, classification, metadata management, and lineage capabilities.

• Design secure identity and access-management models.

• Integrate enterprise authentication and authorization mechanisms.

• Ensure adherence to organizational security, privacy, audit, and compliance standards.

5. Integration & Ecosystem Enablement

• Architect scalable integrations across APIs, streaming platforms, enterprise applications, and data systems.

• Enable secure data sharing and collaboration across internal teams and external partners.

• Define integration patterns supporting both real-time and batch processing.

• Establish standards for reliable and maintainable data movement across the enterprise.

6. Performance, Scalability & Reliability

• Define strategies for high-volume data ingestion and low-latency data processing.

• Design highly available and resilient data platforms.

• Identify and resolve architectural performance bottlenecks.

• Optimize infrastructure and data-processing costs while maintaining performance and reliability.

• Establish architecture standards for scalability, observability, and operational excellence.

7. Stakeholder Leadership & Delivery

• Partner with business, engineering, security, infrastructure, and product teams.

• Lead architecture discussions and technical design reviews.

• Translate business objectives into clear technical solutions and implementation plans.

• Mentor engineering teams and promote architecture and engineering best practices.

• Drive projects from architecture and design through implementation and production delivery.

8. AI/ML, GenAI & Advanced Analytics

• Drive adoption of AI/ML and GenAI capabilities within enterprise data platforms.

• Design data architectures that enable advanced analytics and intelligent automation.

• Enable high-quality, governed, and discoverable data for AI/ML workloads.

• Identify opportunities to leverage emerging technologies to improve business outcomes and operational efficiency.

Ideal Candidate Profile

• 8 10+ years of experience in data architecture, solutions architecture, or enterprise data engineering.

• Strong experience designing enterprise-scale data platforms.

• Hands-on experience with cloud data platforms, data warehouses, and/or lakehouse architectures.

• Proven experience with multi-tenant architecture and data isolation .

• Strong understanding of data governance, security, identity, access control, and compliance.

• Experience with both batch and real-time data processing architectures.

• Strong understanding of data modeling, performance optimization, scalability, and reliability.

• Experience integrating APIs, streaming technologies, and enterprise applications.

• Strong communication, stakeholder-management, and technical leadership skills.

• Experience supporting AI/ML, advanced analytics, or GenAI platforms is highly desirable.

Work Authorization & Location

This is a full-time, on-site position in Santa Clara, California.

Candidates must be authorized to work in the United States and must be one of the following:

• U.S. Citizen

• Green Card Holder

• Green Card EAD Holder

No visa sponsorship or visa transfer is available for this position.

Email: View email address on us.fitly.work