Cloud Engineering Engineer 3

Epitec

$136K — $156K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience in cloud database engineering and architecture
  • Strong knowledge of GCP technologies and services
  • Experience with AI/GenAI concepts and implementations
  • Skilled in automation and DevSecOps practices
  • Familiarity with data compliance standards like GDPR and HIPAA
  • Able to design scalable database architectures using SQL and NoSQL

Responsibilities

  • Lead innovations in AI-driven database solutions
  • Define AI patterns for contextual interactions with databases
  • Implement automation throughout the database lifecycle
  • Collaborate with AI/ML teams to enhance data strategies
  • Establish standards for data metadata and discoverability
  • Promote Data-as-a-Product strategies
  • Ensure compliance with security standards and practices
  • Apply SRE principles for database availability and recovery
  • Tune performance and optimize queries across systems
  • Develop CI/CD pipelines for database deploys
  • Architect solutions across multiple database engines
  • Design ETL pipelines and complex data models
  • Mentor and lead cross-functional engineering teams

Benefits

  • Medical, Dental, Vision insurance
  • Paid Time Off
  • 401K retirement plan
Full Job Description
  • Location: Dearborn, Michigan
  • Type: Contract
  • Job #104478

Job Title: Cloud Engineer

Location: Dearborn, Michigan

Job Type: W2 Contract

Expected hours per week: 40 hours

Schedule: Hybrid (4 days onsite, 1 day remote)

Pay Range (must include "per hour"): $65-75 an hour

Job Description:
We are seeking a Senior Cloud Database Engineer to join our Platform Engineering team, focusing on defining strategy, architecture, and standardized "golden paths" for cloud databases and the AI journey on GCP. This role extends beyond traditional database administration, acting as a technical leader and pattern owner to shape the vision and roadmap while embedding AI/GenAI capabilities into how teams design, build, secure, and operate intelligent data systems at scale.

Key Responsibilities:
  • Lead AI-driven database innovation, including adoption of Gemini Enterprise for query generation, debugging, and schema optimization
  • Define contextual AI patterns by 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 embed ML, statistical models, and GenAI into data platform strategies and build intelligent agents for business value and OLTP cost reduction
  • Establish enterprise standards for metadata, tagging, classification, lineage, and discoverability using Dataplex and Knowledge Catalog
  • Promote Data-as-a-Product with well-documented, discoverable, and consumable datasets
  • Align security and compliance with GDPR, HIPAA, and GCP IAM, including service accounts, role bindings, encryption, and secure agent practices
  • Apply database SRE practices to ensure availability, fault tolerance, and disaster recovery
  • Lead performance tuning, query optimization, indexing strategies, and troubleshooting across distributed systems
  • Enable DevSecOps practices with secure CI/CD pipelines for database code and configurations
  • Define scalable, secure, self-service "golden paths" and database architectures on GCP
  • Build and maintain Terraform templates for automated provisioning and lifecycle management
  • Architect across SQL and NoSQL engines (Cloud SQL, AlloyDB, Spanner, Firestore, Memorystore, MongoDB, BigQuery) with Cloud Functions and Cloud Run
  • Develop complex data models and reliable ETL pipelines integrating multiple data sources
  • Provide cross-team leadership, advising engineering, data, and AI teams, and fostering an AI-assisted, platform-first culture with mentorship

Benefits: Medical, Dental, Vision, PTO & 401K

#LI-MF2
#INDOEM

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