Description

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


6. Performance, Scalability & Reliability
- Define strategies for high-volume data ingestion and low-latency processing


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


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

Key Skills

Education

Bachelor's degree