Description

Define and implement end-to-end data platform architecture across ingestion, storage, transformation, and consumption layers.

This role is on-site.

Responsibilities

• Architect scalable cloud-native data solutions using Lakehouse and Data Mesh patterns, establishing reusable design standards.
• Design multi-tenant data environments with strict isolation, policy-based access control, encryption, and lifecycle management.
• Lead the design of data warehouse and lakehouse platforms, building high-throughput real-time and batch pipelines.
• Define data governance frameworks including cataloging, classification, lineage, and secure identity integration.
• Collaborate with engineering and security teams to translate requirements into architecture roadmaps and mentor delivery teams.

Required Skills

• 13+ years of experience in data engineering, data architecture, or platform engineering.
• Strong expertise in cloud platforms: AWS, Azure, and GCP.
• Hands-on experience with modern data platforms: Databricks, Snowflake, Redshift, or Synapse.
• Proven experience designing and implementing multi-tenant architectures with strong data isolation.
• Deep knowledge of distributed systems, ETL/ELT pipelines, and complex data modeling.
• Experience implementing data governance, security, and compliance frameworks.
• Bachelor's degree in Computer Science or related field.

Preferred Skills

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

Key Skills

Education

Bachelor's degree