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Virtual Google Sql Jobs (NOW HIRING)

BESTPEGASUS LLC

Sr Angular Developer

Albany, NY · On-site

$54.25 - $66.50/hr

Virtual · 84 months of experience creating Angular 8+ applications, including CSS and ReactJS · ... Google Cloud Platform Firebase and Okta · 36 months of experience working with SQL & NoSQL ...

Tanium

Partner Marketing Manager

Addison, TX · Hybrid

Tanium's alliances with Microsoft, AWS, and Google Cloud are among the most important growth levers ... MQL volume and quality, MQL-to-SQL conversion, and partner-sourced and partner-influenced pipeline.

Minnesota Eye

Systems Administrator

Bloomington, MN · On-site

$85K/yr

They will administer, support and deploy core Microsoft, SQL, Azure and Google Cloud servers ... Strong Experience in physical to virtual/cloud Server Migrations * IIS Administration and SSRS ...

Inficare Technologies

Lead AI Engineer

$104K - $138K/yr

AWS Bedrock, Google Vertex AI / Google Cloud AI * Vector databases: Pinecone, Weaviate, ChromaDB ... SQL / NoSQL databases for AI data management * MLOps tools and practices * API development and ...

U-Haul

Digital Marketing Analyst

Phoenix, AZ · On-site

Hands-on experience with Google Analytics 4 * Strong proficiency in HTML, CSS, and SQL ... CVS Virtual Care * UHaul Kids Program * 24Hour Nurse Line * Wellness Program (Healthier You ...

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Virtual Google Sql information

See salary details

$21.5K

$87.6K

$127K

How much do virtual google sql jobs pay per year?

As of Sep 3, 2026, the average yearly pay for virtual google sql in the United States is $87,573.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,500.00 and $100,000.00 per year, depending on experience, location, and employer.

What is a virtual Google SQL?

A Virtual Google SQL job typically refers to a remote position where an individual manages, maintains, and optimizes Google Cloud SQL databases. These professionals are responsible for database administration, backup and recovery, performance tuning, and ensuring data security within Google Cloud environments. The role often involves collaborating with development teams, troubleshooting database issues, and implementing best practices for data management. Virtual Google SQL roles require knowledge of SQL, cloud computing, and experience with Google Cloud Platform services.

What are the key skills and qualifications needed to thrive as a Google Cloud SQL database administrator?

To thrive as a Google Cloud SQL Database Administrator, you need expertise in relational database management, SQL querying, and a deep understanding of Google Cloud Platform (GCP) services. Familiarity with tools like Google Cloud Console, Cloud SQL Admin API, and certifications such as Google Cloud Certified - Professional Data Engineer are highly beneficial. Strong problem-solving skills, attention to detail, and effective communication help you address technical issues and collaborate with diverse teams. These skills are essential for ensuring database reliability, security, and optimal performance in cloud-based environments.

What are some common challenges faced by virtual Google SQL administrators when managing cloud-based databases, and how can they be addressed?

Virtual Google SQL administrators often encounter challenges such as ensuring high availability, optimizing query performance, and managing security in a cloud environment. Handling automated backups, scaling resources efficiently, and monitoring for potential issues are also key responsibilities. These challenges can be addressed by leveraging built-in Google Cloud tools, setting up automated alerts, and adhering to best practices in database design and access control. Collaboration with application developers and cloud architects is crucial to ensure smooth integration and performance.

What is the difference between Virtual Google Sql vs Database Administrator?

AspectVirtual Google SqlDatabase Administrator
CredentialsGoogle Cloud certifications, SQL knowledgeDatabase management certifications (e.g., Oracle, Microsoft)
Work EnvironmentCloud platforms, remote setupOn-premises or cloud, office or remote
Industry UsageCloud service providers, SaaS companiesVarious industries managing data systems
Search/Comparison IntentCloud SQL management, virtual database servicesDatabase management, system administration

Virtual Google Sql involves managing cloud-based SQL databases within Google Cloud, focusing on cloud infrastructure and virtual environments. In contrast, a Database Administrator oversees the entire database lifecycle, including installation, security, and performance, often across on-premises or cloud systems. While both roles require SQL knowledge, Virtual Google Sql specialists focus on cloud-specific skills, whereas Database Administrators have broader database management expertise.

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What are the most commonly searched types of Google Sql jobs?

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Virtual Google Sql jobs near you
Infographic showing various Virtual Google Sql job openings in the United States as of August 2026, with employment types broken down into 84% Full Time, 12% Part Time, and 4% Contract. Highlights an 52% Physical, 2% Hybrid, and 46% Remote job distribution, with an average salary of $87,573 per year, or $42.1 per hour.

Artificial Intelligence Senior Associate

IPS Technology Services

Dearborn, MI • Hybrid

$50 - $55/hr

Full-time

Posted 2 days ago

New

Job description

Job Title: Artificial Intelligence Senior Associate
Location: Dearborn, MI (local preferred)
Duration: 12 Months (with potential for extension)
Interview: Interview onsite in South Lyon/Novi, MI

Candidate must be USC or GC. Do not apply for C2C. It will be a hybrid position. REVIEW JD MAKE SURE REQUIRED SKILLS (highlighted red) ARE ON THE RESUME. Will be onsite 4 days a week.

Position Description:
Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming

Key Responsibilities:
  • Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities
  • Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence
  • Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming
  • Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation

Skills Required:
  • Google Cloud Platform

Experience Required:
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).
  • 3+ years building production software systems, including 1–2+ years on ML/AI or LLM-based applications. Proven experience designing and deploying multi-agent or multi-service architectures in production — not just notebooks or demos.
  • As one 2026 hiring analysis puts it, the job is closer to distributed systems engineering with a probabilistic component than it is to ML research or prompt tweaking .
  • Strong Python proficiency, including async/concurrent programming, and experience with backend frameworks (FastAPI, Flask).
  • Hands-on experience with agent orchestration frameworks — LangGraph, CrewAI, LlamaIndex, or equivalent — for building stateful, multi-step, tool-using agent workflows.
  • Practical experience building RAG pipelines: vector databases (pgvector, Pinecone, Weaviate, or Qdrant), embeddings, chunking strategies, and retrieval evaluation. Cloud deployment experience, ideally Google Cloud Platform (BigQuery, Cloud Run/GKE, Vertex AI, Pub/Sub) or equivalent AWS/Azure services.
  • Strong SQL skills and experience with cloud data warehouses. Containerization and CI/CD experience (Docker, Kubernetes, GitHub Actions/Cloud Build).
  • Experience building evaluation and observability pipelines for LLM/agent systems — offline eval sets, LLM-as-judge scoring, and tracing tools (LangSmith, Langfuse, OpenTelemetry, or equivalent) to track task success, latency, and cost.
  • Understanding of LLM safety practices: guardrails, output validation, prompt-injection defense, and safe execution of AI-generated code/SQL (sandboxing, least privilege). Solid software engineering fundamentals: API design, testing, version control, security best practices.

Experience Preferred:
  • Experience with cost optimization and model routing — designing tiered pipelines that route between low-cost and high-capability models based on task complexity, and modeling per-conversation or per-task cost at scale.
  • Experience deploying agentic systems with human-in-the-loop or multi-checkpoint validation workflows for high-reliability/high-stakes use cases.
  • Experience with automotive, EV charging, IoT, or connected-vehicle telemetry data.
  • Familiarity with Model Context Protocol (MCP) or similar standards for tool/data integration across agents.
  • Prior experience in a startup or 0-to-1 product environment, comfortable with ambiguity and fast-evolving requirements.
Education Required:
  • Bachelor's Degree

Education Preferred:
  • Master's Degree

Additional Information:
  • Architect and deploy the production multi-agent orchestration layer (interpreter/orchestrator, NL-to-SQL agent, visualization agent, RCA/RAG agent, report composition agent, notification agent), using modern agent frameworks with state management and checkpointing rather than ad-hoc loops.
  • Design and productionize RAG pipelines (chunking, embeddings, hybrid retrieval, reranking) grounded in approved schemas, engineering documentation, and historical issue records.
  • Own BigQuery integration and enforce safe, least-privilege, validated execution of LLM-generated SQL. Build CI/CD, containerization, and infrastructure-as-code for deploying agent services on GCP (Cloud Run/GKE, Vertex AI).
  • Implement evaluation pipelines and observability/tracing for every agent (golden datasets, LLM-as-judge scoring, regression alerts) so quality is measurable, not assumed.
  • Implement guardrails, prompt-injection defenses, and human-in-the-loop approval checkpoints to ensure correctness and safety before any output triggers downstream action. Design cost/latency optimization strategies, including tiered model routing (cheap filter models vs. high-capability deep-dive models) and caching.
  • Integrate validated outputs with operational systems (Salesforce ticketing, driver/site-manager notifications) and report export pipelines (PDF/HTML/spreadsheet).
  • Collaborate with data scientists to productionize prototypes (anomaly detection, diagnostic agents) into scalable, monitored services.
  • Establish versioning, testing, and safe rollout practices (canary/shadow deployments) for evolving agent logic.


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About IPS Technology Services

Sourced by ZipRecruiter

In today's Tech driven world, Businesses and Organizations need to stay on the cutting edge to thrive and outshine the competition. We at IPS Technology Services fully understand the need today's business has for a full spectrum of IT services delivered in a Transparent, Cost effective way. Our dedicated team has many combined years of experience in several tech sectors, allowing us to offer a vast array of services, including IT staffing, CIO advisory, Digital marketing, Systems development and both Healthcare and engineering IT. In addition, we even offer IT outsourcing services to clients who need operation support for older systems that they still rely on. We will never force you to abandon the system that works for your needs–at IPS Technology Services, we fully understand that each company is different and there is no one-size fits all solution.

Company size

11 - 50 Employees

Headquarters location

Troy, MI, US

Year founded

2004

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