Description

Define and implement end-to-end data platform architecture, including ingestion, storage, transformation, and consumption layers for scalable cloud-native solutions.

This role is on-site.

Responsibilities

• Architect multi-tenant data environments with strict data isolation, policy-based access control, and encryption strategies.
• Lead the design and implementation of data warehouse and lakehouse platforms, ensuring high throughput and low latency.
• Establish data governance frameworks, including cataloging, classification, lineage, and secure identity integration.
• Design scalable integration for APIs, streaming platforms, and enterprise systems while optimizing data models and query performance.
• Mentor engineering teams, translate business requirements into architecture roadmaps, and drive best practices across security and infrastructure.

Required Skills

• 12+ years of experience in data engineering, data architecture, or platform engineering.
• Strong expertise in cloud platforms: AWS, Azure, GCP.
• Hands-on experience with modern data platforms: Databricks, Snowflake, Redshift, Synapse.
• Proven 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 Skills

• Experience with lakehouse architectures and GenAI/Agentic AI frameworks.
• Familiarity with policy-based access models and identity systems.
• Experience in semiconductor, manufacturing, or high-tech industries.

Key Skills

Education

Bachelor's degree