Lead Data Engineer

Lead Data Engineer with Agentic AI experience Core must-haves (screen for these explicitly)

• Applied Agentic AI engineering experience: evidence of building Agentic workflows - ideally delivered into a real project.
• Modern multi-agent architecture experience: hands‑on designing/implementing systems where multiple AI Agents collaborate.
• Strong understanding of agentic frameworks/tools: candidates must be able to name the frameworks used, explain why chosen, and describe components.
• Protocols knowledge with practical relevance: working knowledge (preferably applied) of MCP, A2A, ACP—and ability to explain how they're used in real‑world AI Agent systems.
• Architecture & design contribution capability: candidate should be able to contribute to solution architecture, discuss trade‑offs/pros‑cons, and guide design decisions for agentic systems.
• Proficiency in Google Big Query for data warehousing and analytics.
• Strong SQL skills for querying and managing large datasets.
• Advanced knowledge of Python programming language for data manipulation and analysis.
• Experience with Google Dataflow for real‑time data processing and ETL pipelines.
• Strong problem‑solving and analytical skills.
• Excellent communication and leadership abilities to effectively lead a technical team.