Data Solutions Architect

Job Title: Data Solutions Architect
Duration- Fulltime Permanent
Location: Santa Clara, CA (Onsite From Day 1)

Job Description:
We are seeking a highly experienced Data Solutions Architect to design and deliver next-generation cloud-based data platforms with a strong focus on data warehousing, lakehouse architectures, and multi-tenant enablement.
This role will drive architecture strategy and execution for scalable, secure, and high-performance data solutions, enabling advanced analytics, AI/ML, and cross-organization collaboration.
The ideal candidate will bring hands-on experience in cloud data platforms, enterprise data architecture, and multi-tenant system design, along with the ability to translate business requirements into robust technical solutions

Must Have Technical/Functional Skills:
1. Architecture & Design
- Define and implement end-to-end data platform architecture across ingestion, storage, transformation, and consumption layers
- Design scalable cloud-native data solutions using modern architectures such as Lakehouse and Data Mesh
- Establish reference architectures and reusable design patterns

2. Multi-Tenant Platform Implementation
- Architect multi-tenant data environments with strong data isolation and segregation
- Implement policy-based access control and encryption strategies
- Enable customer onboarding models, tenant provisioning, and lifecycle management
- Ensure compliance with security, audit, and regulatory requirements

3. Cloud Data Platform & Data Warehouse
- Lead design and implementation of data warehouse and lakehouse platforms
- Architect real-time and batch data pipelines with high throughput and low latency
- Optimize data models, query performance, and data workflows

4. Data Governance, Security & Compliance
- Define data governance frameworks including data cataloging, classification, and lineage
- Implement secure access control models and identity integration
- Ensure adherence to enterprise security and compliance standards

Key Responsibilities:
5. Integration & Ecosystem Enablement
- Design scalable integration for APIs, streaming platforms, and enterprise systems
- Enable seamless data sharing and collaboration across teams and external partners

6. Performance, Scalability & Reliability
- Define strategies for high-volume data ingestion and low-latency processing
- Optimize cost, performance, and scalability of data platforms

7. Stakeholder Leadership & Delivery
- Collaborate with business, engineering, security, and infrastructure teams
- Translate requirements into architecture roadmaps and implementation plans
- Mentor engineering teams and drive best practices

8. Innovation & Advanced Analytics
- Drive adoption of AI/ML and GenAI solutions in data platforms
- Enable intelligent automation and advanced analytics capabilities & nbsp;