DATA SOLUTIONS ARCHITECT

Role - DATA SOLUTIONS ARCHITECT


Location: Santa Clara, CA


Full Time - Permanent


Experience Required - 08 - 10 Years

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
  
  
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