About the Role
We are seeking a Technical Life Sciences Consultant to drive AI-led business transformation for a leading pharmaceutical client in New York City.
This role sits at the intersection of data governance, cloud architecture, AI foundations, and commercial pharma. You will partner with senior business and technology stakeholders, data product owners, architects, and engineering teams to define enterprise data strategies and build scalable, secure, governed, and AI-ready data platforms.
The ideal candidate combines strong life sciences/pharmaceutical consulting experience with deep knowledge of data governance, cloud architecture, metadata, lineage, data quality, and modern data platforms.

Key Responsibilities
Client & Stakeholder Leadership
Lead senior client workshops focused on problem framing, data strategy, solution design, and transformation roadmaps.
Partner with business and technical stakeholders to understand requirements and translate them into scalable technology solutions.
Provide end-to-end technical advisory across complex data, cloud, and AI transformation programs.
Establish strong relationships with VP, Executive Director, and senior technology/business stakeholders.
Support RFP/RFI responses, solution proposals, architecture assessments, and opportunity development.
Identify opportunities to improve data maturity, platform adoption, governance, and AI readiness.
Data Governance & Strategy
Define and implement enterprise data governance frameworks, standards, and operating models.
Establish standards for metadata management, data lineage, data quality, data classification, and data ownership.
Define governance patterns that enable trusted, discoverable, secure, and AI-ready data.
Develop data models and governance strategies supporting analytical and operational workloads.
Assess current-state data environments and define future-state governance and architecture models.
Partner with data product owners and engineering teams to embed governance into data platforms and products.
Cloud & Data Architecture
Design and guide modern, cloud-native data platforms using AWS and modern data technologies.
Define scalable architectures for analytical, operational, and AI/ML workloads.
Establish architectural standards and reusable patterns for security, scalability, reliability, performance, and cost optimization.
Evaluate technology options and provide recommendations for long-term data and cloud strategies.
Guide engineering teams through architecture reviews, implementation decisions, and technical execution.
Support cloud migration, modernization, and enterprise data platform initiatives.
AI Foundations
Help establish the data and technology foundations required for enterprise AI adoption.
Define data architectures supporting AI/ML, analytics, and advanced commercial pharma use cases.
Establish standards for metadata, context, lineage, quality, and governance required for trusted AI.
Support the design of operational, context, and ontology layers within modern data platforms.
Drive adoption of modern data and AI practices across enterprise teams.
Engineering & Operational Excellence
Define and promote CI/CD, DevOps, testing, monitoring, and observability practices.
Establish frameworks for data quality monitoring, platform reliability, and operational excellence.
Partner with engineering teams to ensure solutions are production-ready, scalable, secure, and cost efficient.
Promote reusable architecture patterns and engineering best practices across delivery teams.
Required Qualifications
10+ years of experience in data architecture, data engineering, AI, software development, or related technology disciplines.
5+ years of life sciences/pharmaceutical consulting experience, preferably within commercial pharma.
Strong experience with enterprise data governance and data architecture.
Deep understanding of metadata, lineage, data quality, data standards, and governance frameworks.
Strong knowledge of AWS and cloud-native data architectures.
Experience with modern data platforms and technologies such as Databricks, Spark, SQL, Python, and/or dbt.
Experience designing scalable data models for analytical and operational workloads.
Experience with cloud migration and data platform modernization.
Strong understanding of distributed computing and modern data engineering patterns.
Experience with CI/CD, DevOps, testing, monitoring, observability, and operational excellence.
Excellent communication, presentation, and stakeholder management skills.
Ability to lead multi-team delivery across onsite/offshore environments.
Preferred Qualifications
Commercial pharmaceutical data and business domain experience.
Experience building AI foundations and AI-ready enterprise data platforms.
Experience with AWS services such as S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis.
Experience with Databricks and dbt Core/Cloud.
Knowledge of Data Vault 2.0 and/or automate_dv.
Experience with ontology, context, semantic, or knowledge layers.
Experience defining enterprise data operating models and governance organizations.
Experience working with senior pharma executives and technology leadership.
Strong experience leading architecture workshops and technical visioning sessions.

What You'll Bring
We are looking for a consultative technology leader who can connect business strategy with enterprise data and cloud architecture.
You should be comfortable leading an executive discussion about data strategy and governance, translating those requirements into an architecture, and partnering with engineering teams to drive successful implementation.
This is an opportunity to help shape AI-ready data foundations for a leading pharmaceutical organization while working on large-scale cloud modernization, data governance, and commercial pharma transformation initiatives.
Compensation & Benefits

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Technical Life Sciences Consultant – Data Governance, Cloud & Commercial Pharma

Bestica Inc.

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