Role: Data Solutions Architect – Cloud Data Platform & Multi Tenancy

Location: Santa Clara, CA - Onsite

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.

Key Responsibilities

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

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

Required Qualifications

- 12+ years of experience in data engineering, data architecture, or platform engineering

- Strong expertise in cloud platforms (AWS, Azure, GCP)

- Experience with modern data platforms (Databricks, Snowflake, Redshift, Synapse, etc.)

- Hands-on experience with multi-tenant architecture design and implementation

- Strong knowledge of distributed systems, ETL/ELT pipelines, and data modeling

- Experience with data governance, security, and compliance frameworks

Preferred Qualifications

- Experience with lakehouse architectures and modern data platforms

- Familiarity with policy-based access models and identity systems

- Experience in semiconductor, manufacturing, or high-tech industries

- Exposure to GenAI or Agentic AI frameworks

Success Criteria:

- Successful deployment of scalable, multi-tenant data platforms

- Improvements in data latency, performance, and quality

- Adoption of secure, governed, and reusable architecture patterns

- Enablement of data-driven decision making and advanced analytics

Regards,

Kartik Sana

sana@realtekconsulting.net