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Remote Vp Data Center Operations Jobs (NOW HIRING)

VP, Data & Analytics

New York, NY · Remote

$196K - $253K/yr

About the role LifeMD is seeking a visionary and execution-focused Vice President of Data ... Build and scale modern cloud-native data platforms supporting operational, clinical, product, and ...

Collaborate with delivery and operations teams to ensure seamless execution and client satisfaction ... REQUIRED EXPERIENCE 10+ years in data center colocation sales, with 3+ years focused on Hyperscale ...

VP, Data Science

$235K - $336K/yr

The VP of Data Science & Analytics will lead experimentation, business intelligence, and advanced ... This role is fully remote and not tied to any specific office location. While there are no regular ...

Cayenta, a division of Harris; is seeking a Vice President of Research & Development who is a ... operational realities of a large, profitable install base. The leader who succeeds will do so by ...

Cayenta, a division of Harris; is seeking a Vice President of Research & Development who is a ... operational realities of a large, profitable install base. The leader who succeeds will do so by ...

Cayenta, a division of Harris; is seeking a Vice President of Research & Development who is a ... operational realities of a large, profitable install base. The leader who succeeds will do so by ...

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Remote Vp Data Center Operations information

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$68.5K

$155.8K

$264K

How much do remote vp data center operations jobs pay per year?

As of Jul 21, 2026, the average yearly pay for remote vp data center operations in the United States is $155,780.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $185,000.00 per year, depending on experience, location, and employer.
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What cities are hiring for Remote Vp Data Center Operations jobs? Cities with the most Remote Vp Data Center Operations job openings:
What are the most commonly searched types of Vp Data Center Operations jobs? The most popular types of Vp Data Center Operations jobs are:
Infographic showing various Remote Vp Data Center Operations job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $155,780 per year, or $74.9 per hour.
VP, Data & Analytics

VP, Data & Analytics

LifeMD

New York, NY • Remote

$196K - $253K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago


Job description

About us

LifeMD is transforming healthcare through intelligent digital experiences, AI-powered virtual care, and connected healthcare platforms. Our mission is to make high-quality healthcare more accessible, personalized, and convenient by combining world-class clinical care with modern technology and data-driven innovation.

As we continue to scale, we are investing in the next generation of AI, data, and platform capabilities that will fundamentally reshape how healthcare is delivered, experienced, and operated.

About the role

LifeMD is seeking a visionary and execution-focused Vice President of Data, Analytics & AI to lead the company's enterprise data and artificial intelligence strategy. Reporting to the Chief Technology Officer, this executive will build the next-generation data and AI platform that powers every aspect of LifeMD-from patient experiences and clinical operations to internal productivity, intelligent automation, and business decision-making.

This is a hands-on Data engineering leadership role for someone who has successfully taken data and AI initiatives from proof of concept to enterprise production. The ideal candidate is equally comfortable discussing distributed data architectures, Retrieval-Augmented Generation (RAG), AI agents, LLM orchestration, analytics strategy, data engineering vision, and executive business priorities.

You will lead multidisciplinary teams across Data Engineering, Analytics Engineering, AI Engineering, Machine Learning, and Business Intelligence while partnering closely with Product, Engineering, Clinical Operations, Marketing, Finance, Compliance, and Security.

What You Will Own

Enterprise Data Platform

  • Define and execute LifeMD's enterprise data strategy and roadmap
  • Build and scale modern cloud-native data platforms supporting operational, clinical, product, and financial workloads
  • Design robust batch and real-time data pipelines across healthcare, product, pharmacy, CRM, marketing, finance, and operational systems
  • Establish enterprise data models, governance, metadata management, and data quality frameworks
  • Enhance self-service analytics and trusted enterprise reporting

Artificial Intelligence & GenAI

  • Lead LifeMD's enterprise AI strategy and production deployment roadmap
  • Build secure enterprise Retrieval-Augmented Generation (RAG) platforms leveraging proprietary healthcare knowledge and enterprise content
  • Design, deploy, and manage AI agents that automate clinical, operational, customer support, engineering, finance, HR, and internal business workflows
  • Establish scalable LLMOps and AI engineering practices supporting multiple foundation models and vendors
  • Lead evaluation, experimentation, and production deployment of emerging AI technologies
  • Develop AI governance frameworks focused on safety, explainability, privacy, compliance, and responsible AI adoption

Knowledge Platforms & Intelligent Automation

  • Build enterprise knowledge management capabilities supporting employees, providers, and customer-facing applications
  • Develop internal AI copilots that improve productivity across engineering, customer care, operations, and clinical organizations
  • Build intelligent search capabilities powered by vector databases and semantic retrieval
  • Lead Model Context Protocol (MCP) architecture and governance to enable secure interoperability between AI models, enterprise systems, tools, and knowledge sources
  • Drive automation initiatives that reduce manual work, improve operational efficiency, and accelerate decision-making

Data Engineering & Analytics

  • Lead enterprise data engineering and analytics teams
  • Build scalable ELT/ETL pipelines supporting healthcare operations and business intelligence
  • Develop executive dashboards and real-time operational insights across patient engagement, provider performance, finance, product, marketing, and growth
  • Establish KPIs and measurement frameworks supporting customer experience, healthcare outcomes, operational efficiency, and business performance
  • Enable experimentation, predictive analytics, forecasting, and AI-driven decision support

Leadership

  • Recruit, mentor, and develop high-performing teams across Data Engineering, Analytics Engineering, AI Engineering, Machine Learning, and Business Intelligence
  • Foster a culture of experimentation, engineering excellence, innovation, continuous learning, and customer obsession
  • Partner closely with Product Management, Engineering, Clinical Operations, Security, Legal, and Compliance to ensure scalable and compliant AI adoption
  • Communicate technology strategy and business outcomes effectively to executive leadership and the Board of Directors

Requirements

  • 12+ years of experience leading enterprise data, analytics, AI, or machine learning organizations
  • 5+ years leading large engineering organizations responsible for enterprise data platforms and AI systems
  • Proven experience deploying Generative AI solutions from proof of concept through enterprise production
  • Deep expertise building Retrieval-Augmented Generation (RAG) architectures using vector databases, embeddings, enterprise knowledge repositories, and LLM orchestration frameworks
  • Experience designing and deploying AI agents, workflow automation platforms, and intelligent assistants
  • Strong understanding of MCP (Model Context Protocol), agent orchestration, prompt engineering, and modern AI application architectures
  • Hands-on experience with modern cloud data platforms such as Snowflake, BigQuery, Databricks, or equivalent
  • Strong programming experience in Python, SQL, APIs, distributed systems, and modern data engineering frameworks
  • Experience with cloud-native architectures (AWS, Azure, or Google Cloud)
  • Experience implementing LLMOps, MLOps, CI/CD, model evaluation, monitoring, observability, and governance frameworks
  • Strong knowledge of healthcare data, HIPAA, PHI security, privacy, and regulatory compliance preferred
  • Experience leading enterprise analytics, experimentation, KPI development, and executive reporting
  • Exceptional communication, organizational, and executive leadership skills

Benefits

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (Roth 401k)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Flexible PTO Policy
  • Paid Holidays
  • Short Term Disability
  • Training & Development