Python Data Engineer

Key Responsibilities

• Build multi-agent orchestration frameworks with memory and caching layers
• Design and instrument knowledge graph architectures for agent reasoning
• Develop conversational analytics using Gemini Enterprise, Google ADK, and MCP
• Configure BigQuery Data Agents and address data quality/deep research issues
• Implement end-to-end security and observability for production agents
• Build ETL/ELT pipelines and analytics-ready datasets on GCP

Required Qualifications

AI & Agents

• Strong understanding of LLMs, agentic AI, multi-agent orchestration, and tool-calling concepts
• Experience building with at least one LLM platform (Gemini, OpenAI, Anthropic, etc.) and exposure to modern agent frameworks
• Familiarity with RAG architectures, agent memory systems, and prompt engineering through projects or self-directed learning
• Strong foundation in software engineering that transfers well to agent systems development

Data Engineering

• Advanced SQL and BigQuery expertise
• Experience building ETL/ELT pipelines and designing semantic models
• Knowledge of modern cloud data warehouse architectures

Software Development

• Strong Python development skills
• Experience with APIs, distributed systems, Docker

GCP & Operations

• Working knowledge of GCP services (Compute, Storage, Data, ML/AI)
• Understanding of cloud security best practices
• Experience implementing observability and monitoring

Nice-to-Have

• Vector databases, Vertex AI, or knowledge graph experience
• Background in internal developer platforms or analytics infrastructure