Tech Stack

Description

You will own the end-to-end AI-first data platform architecture, designing real-time streaming systems and lakehouse patterns to power intelligent products, ML models, and operational workflows. This role is a technical authority that sets architectural direction across streaming, storage, and serving layers for AI and real-time analytics.

Requirements

• Senior-level experience building data platforms with streaming and lakehouse architectures
• Deep technical expertise in AWS (Kinesis, S3, IAM, networking) and Databricks (clusters, jobs, Delta Lake)
• Experience designing real-time streaming systems for AI/ML use cases
• Ability to set architectural direction and act as a technical authority
• Strong collaboration skills with engineering, analytics, data science, and product teams

Responsibilities

• Own end-to-end AI-first data platform architecture spanning streaming, lakehouse storage, and serving layers
• Architect real-time streaming systems using AWS Kinesis and Spark Structured Streaming for low-latency AI and ML inference
• Design stream-to-lakehouse convergence patterns unifying real-time and historical data with strong correctness guarantees
• Build and evolve data, metrics, and feature APIs for AI-ready datasets
• Establish canonical event schemas, feature definitions, and data contracts for event-driven systems and ML