GCP Data Engineer

Stefanini GroupDearborn, MI
Onsite

About The Position

Stefanini Group is hiring! Stefanini is looking for a GCP Database Engineer (Dearborn, MI). We are seeking a Senior Cloud Database Engineer to join our Platform Engineering team. This role focuses on defining strategy, architecture, and standardized “golden paths” for cloud databases and the AI journey on Google Cloud Platform (GCP). You will act as a technical leader, shaping the vision and roadmap for our database platform, with a key focus on embedding AI/GenAI capabilities (e.g., Gemini Enterprise, Model Context Protocol, Dataplex, and Knowledge Catalog) into how engineering teams design, build, secure, and operate intelligent data systems at scale.

Requirements

  • GCP Skills
  • Artificial Intelligence & Expert Systems Experience
  • 6+ years of experience in IT; 4+ years in development.
  • 5+ years in database engineering with a focus on GCP AI enablement.
  • Experience with Gemini Enterprise and understanding of MCP or equivalent patterns.
  • Hands-on experience with GCP databases including Cloud SQL, AlloyDB, Spanner, Firestore, Memorystore, MongoDB, and BigQuery.
  • Knowledge of GCP IAM, encryption, and CI/CD practices.
  • Experience building Internal Developer Platforms (IDPs).
  • GCP Professional Cloud Database Engineer or Data Engineer.
  • Proficiency in Terraform and programming (Python/Java).
  • Experience with Kubernetes (GKE) and database operators.
  • Understanding of statistical analysis, data modeling, and ML libraries.
  • Bachelor's Degree

Responsibilities

  • Lead adoption of Gemini Enterprise for query generation, debugging, and schema optimization.
  • Define patterns for integrating Model Context Protocol (MCP) with databases for contextual AI interactions.
  • Identify and implement AI-driven automation across the database lifecycle, including capacity planning, anomaly detection, and self-tuning.
  • Partner with AI/ML teams to integrate ML, statistical models, and GenAI into data platform strategies.
  • Build intelligent agents on database AI frameworks to improve fault detection and reduce OLTP costs.
  • Establish enterprise standards for metadata, including tagging, classification, lineage, and discoverability.
  • Promote well-documented, discoverable datasets.
  • Align with GDPR and HIPAA frameworks; manage GCP IAM, service accounts, role bindings, and encryption.
  • Apply reliability practices to ensure availability, fault tolerance, and disaster recovery.
  • Lead query optimization, indexing strategies, and troubleshooting across distributed systems.
  • Enable secure CI/CD pipelines for database code and configurations.
  • Establish scalable, secure, self-service database architectures on GCP.
  • Build and maintain Terraform templates for automated provisioning and lifecycle management.
  • Architect across SQL (SQL Server, PostgreSQL, MySQL, AlloyDB, Spanner) and NoSQL (MongoDB, Firestore, Bigtable, Memorystore, Neo4j) with Cloud Functions and Cloud Run.
  • Develop complex data models and reliable ETL pipelines integrating multiple data sources.
  • Advise engineering, data, and AI teams on best practices.
  • Foster an AI-assisted, platform-first culture and mentor engineers.
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service