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 ...
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 ...
Vice President Centrix information
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$43.5K - $64.8K
1% of jobs
$64.8K - $86K
5% of jobs
$86K - $107.3K
14% of jobs
$113.3K is the 25th percentile. Wages below this are outliers.
$107.3K - $128.6K
18% of jobs
The median wage is $142.2K / yr.
$128.6K - $149.9K
19% of jobs
$149.9K - $171.1K
14% of jobs
$180.2K is the 75th percentile. Wages above this are outliers.
$171.1K - $192.4K
11% of jobs
$192.4K - $213.7K
8% of jobs
$213.7K - $235K
4% of jobs
$235K - $256.2K
4% of jobs
$256.2K - $277.5K
2% of jobs
$43.5K
$157.5K
$277.5K
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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