Technical Life Sciences Consultant, Pharma (Business Translator)

Cephas Consultancy Services Private Limited

United States, New Jersey | United States, New York

On-site · Full-time

Role Overview

Location: New York and New Jersey

Experience: 10–15 years

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. This role leverages enterprise-scale data and platform architectures on AWS and Databricks. You will be responsible for end-to-end client management, program management, business growth, and client success, ensuring solutions are scalable, secure, cost-efficient, and aligned with modern data engineering, analytics, and AI/ML best practices. You 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

  • Bring experience with life sciences datasets, migration, and modernization.
  • Understand operational layers (L1, L2, and L3), as well as 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 a 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, including 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 is 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.

Compensation

  • Annual variable bonus: 15%

Benefits

  • Health, dental, vision, life, and disability insurance.
  • Benefits start on the first day of employment.
  • 401(k) eligibility after 30 days of employment.
  • 11 paid holidays.
  • 12 weeks of parental leave.
  • Flexible PTO policy for vacation and sick leave.