Cloud Database Engineer Google Cloud Platform & AI Strategy

N2 Services Inc

yesterday

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Experience level

Senior

Remote

Artificial Intelligence

Google BigQuery

Databases

Continuous Integration

Data Governance

Software Debugging

Identity and Access Management

Metadata

MongoDB

Online Transaction Processing

Google Cloud Platform

Generative AI

Devsecops

Software Library

1. AI-Driven Database Innovation GenAI Productivity: Lead the adoption of Gemini Enterprise for database engineering productivity (e.g., automated query writing, debugging, and schema optimization).
Contextual AI Patterns: Define and implement patterns for integrating the Model Context Protocol (MCP) with databases to enable seamless, contextual AI interactions.
Intelligent Automation: Identify and deploy AI-driven automation opportunities across the database lifecycle, including predictive capacity planning, anomaly detection, and self-tuning.
AI/ML Collaboration: Partner with AI/ML teams to embed machine learning libraries, statistical modeling, and GenAI capabilities into broader data platform strategies.
Agent Development: Build agents on top of database AI framework that drive business value fault detection and cost reduction in the OLTP space at source and instant value realization.

Bachelor Degree is REQUIRED
5+ years in database engineering with Google Cloud Platform AI enablement focus.
AI/GenAI Familiarity: Experience with Gemini Enterprise (or similar) and understanding of MCP or equivalent patterns.
Data Governance: Experience with Dataplex and Knowledge Catalog for metadata and lineage.
Multi-Engine Proficiency: Hands-on experience with Google Cloud Platform databases including Cloud SQL, AlloyDB, Spanner, Firestore, Memorystore, MongoDB, and BigQuery.
Security & DevSecOps: Knowledge of Google Cloud Platform IAM, encryption, and CI/CD practices.