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Vice President Centrix Jobs (NOW HIRING)

Vice President Centrix information

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$43.5K

$157.5K

$277.5K

How much do vice president centrix jobs pay per year?

As of Aug 17, 2026, the average yearly pay for vice president centrix in the United States is $157,532.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,000.00 and $190,000.00 per year, depending on experience, location, and employer.

What are the most commonly searched types of Centrix jobs?

The most popular types of Centrix jobs are:

What states have the most Vice President Centrix jobs?

States with the most job openings for Vice President Centrix jobs include:

Technical Life Sciences Consultant ​​​​​

V-CENTRIX-US LLC

Jersey City, NJ • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

Role Overview

We are seeking a Technical Life Sciences Consultant to drive AI-led business transformations for Fortune 50 Life Sciences clients in New York and New Jersey, using enterprise-scale data and platform architectures on AWS and Databricks.

The role is responsible for end-to-end client management, program management, business growth, and client success by ensuring solutions are scalable, secure, cost-efficient, and aligned with modern data engineering, analytics, and AI/ML best practices. The consultant will partner with engineering teams, data product owners, and business stakeholders to establish architectural standards, design cloud-native data platforms, and guide technical execution across complex programs.

Roles and Responsibilities

Stakeholder Engagement

  • Drive senior client workshops, problem framing, and solution framing
  • Lead end-to-end client advisory, opportunity creation, and demand generation
  • Engage with business and technical teams to align architecture with business requirements
  • Support RFP and RFI responses and architectural evaluations

AI Foundations in Pharma

  • Experience with Life Sciences datasets, migration, and modernization
  • Understanding of operational layers L1, L2, and L3, along with ontology and context layers
  • Define and enforce data modeling, metadata, lineage, and quality standards
  • Implement CI/CD pipelines and monitoring frameworks
  • Ensure architectures support observability, reliability, and operational excellence
  • Architect end-to-end solutions on AWS and Databricks
  • Define architectural standards, patterns, and best practices
  • Review and guide solution designs for scalability, performance, and security
  • Evaluate technology options and recommend long-term architectural strategies
  • Translate business and analytical requirements into scalable data models
  • Assess current-state data architectures and define future-state models
  • Design scalable data models for analytical and operational workloads
  • Demonstrate strong understanding of metadata, lineage, data quality, and governance frameworks
  • Be familiar with distributed compute paradigms and cloud-native modeling patterns

Qualifications

Core Technical Expertise

  • 10+ years of experience in AI, software development, data engineering, or data architecture
  • 5+ years of Life Sciences consulting experience
  • Experience driving modernization initiatives for AI products with AI foundations, governance, operational layers, and context layers
  • Strong experience with Databricks, dbt Core or Cloud, Python, Spark, SQL, distributed compute paradigms including in-memory, distributed, and MPP architectures, and Data Vault 2.0 including automate_dv
  • Deep knowledge of AWS services including S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis

Leadership and Collaboration

  • Experience leading architecture across multi-team onsite and offshore delivery models
  • Executive presence to lead VP and Executive Director-level meetings and steering committees independently
  • Ability to drive thought leadership, technical visioning, workshops, and client success initiatives
  • Life Sciences experience preferred

AI Foundations

  • Ability to translate complex analytical requirements into scalable architectures including data models, ETL pipelines, and consumption layers
  • Experience designing and deploying dashboards and self-service analytics on relational and non-relational databases
  • Strong understanding of CI/CD, DevOps, static code analysis, and test-driven development
  • Experience with cloud migration patterns and modern data platform design
  • Experience defining data standards, metadata models, lineage, quality rules, and governance patterns
  • Experience implementing logging, monitoring, observability, and cost optimization frameworks
  • Experience driving enterprise data platform adoption and modern data practices