Technical Life Sciences Consultant – AI, AWS & Databricks

About the Role

We are seeking a Technical Life Sciences Consultant to lead AI-driven business transformation and modern data platform initiatives for major Life Sciences and Pharmaceutical clients. This role combines hands-on technical architecture with client consulting, executive stakeholder management, solution design, and technical leadership across complex enterprise data and AI programs.

Responsibilities

• Client & Stakeholder Leadership
  • Lead senior client workshops, discovery sessions, problem framing, and solution framing.
  • Partner with business, technical, engineering, and data teams to translate business requirements into scalable technical solutions.
  • Lead client advisory engagements and support opportunity creation and demand generation.
  • Support RFP/RFI responses, architecture assessments, and technology evaluations.
  • Present technical strategies and recommendations to senior client stakeholders and executive leadership.
  • Drive technical vision, thought leadership, and client success.
• Life Sciences & AI Foundations
  • Lead modernization initiatives for AI products and enterprise data platforms within the Life Sciences domain.
  • Work with Life Sciences and pharmaceutical datasets, migration initiatives, and modernization programs.
  • Design AI foundations incorporating data, governance, operational, ontology, and context layers.
  • Define standards for data modeling, metadata, lineage, data quality, and governance.
  • Translate complex analytical and business requirements into scalable data models, pipelines, and consumption layers.
  • Support enterprise adoption of modern AI and data practices.
• AWS & Databricks Architecture
  • Architect end-to-end cloud-native data and AI solutions using AWS and Databricks.
  • Define reusable architecture patterns, standards, and best practices.
  • Review technical designs for scalability, performance, security, reliability, and cost efficiency.
  • Evaluate technology options and recommend long-term architectural strategies.
  • Assess current-state data architectures and define future-state models.
  • Design data platforms supporting both analytical and operational workloads.
• Data Engineering & Architecture
  • Work with Databricks, dbt Core/Cloud, Python, Spark, and SQL.
  • Apply distributed computing paradigms including in-memory, distributed, and MPP architectures.
  • Design scalable ETL/ELT pipelines and modern data platforms.
  • Apply Data Vault 2.0, including automate_dv.
  • Define data models and consumption layers for analytics and AI applications.
  • Establish metadata, lineage, data quality, and governance frameworks.
  • Drive enterprise data platform modernization and adoption.
• AWS Technologies

  Experience with several of the following AWS services is required:

  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon EMR
  • Amazon DynamoDB
  • AWS Lambda
  • Amazon Athena
  • Amazon Kinesis
• DevOps & Operational Excellence
  • Design and support CI/CD pipelines for data and AI platforms.
  • Apply DevOps, static code analysis, and test-driven development practices.
  • Establish logging, monitoring, observability, and operational excellence frameworks.
  • Support reliability, performance, security, and cost optimization initiatives.
  • Implement cloud migration and modernization patterns.
• Technical Leadership
  • Lead architecture across multi-team onsite and offshore delivery models.
  • Provide technical direction and architectural guidance to engineering teams.
  • Lead technical workshops and solution visioning sessions.
  • Mentor technical teams and promote modern data engineering practices.
  • Independently lead meetings with VP and Executive Director-level stakeholders.
  • Manage multiple priorities across complex enterprise programs.

Requirements

• 10+ years of experience in AI, software development, data engineering, data architecture, or related technical fields.
• 5+ years of Life Sciences consulting experience.
• Proven experience driving AI product modernization and enterprise data platform transformation.
• Strong experience with Databricks.
• Strong experience with dbt Core or dbt Cloud.
• Strong hands-on experience with:
  • Python
  • Spark
  • SQL
• Strong understanding of distributed computing, including:
  • In-memory computing
  • Distributed computing
  • MPP architectures
• Strong experience with Data Vault 2.0. Experience with automate_dv is highly preferred.
• Strong AWS knowledge with services such as S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis.
• Experience designing modern cloud-native data platforms.
• Experience with data migration and cloud modernization.
• Strong knowledge of data modeling, metadata, lineage, data quality, and governance.
• Experience with CI/CD and DevOps practices.
• Strong understanding of logging, monitoring, observability, and cost optimization.
• Excellent communication, consulting, problem-solving, and stakeholder management skills.

Skills

• Design
• Architecture
• Modernization
• Data
• Cloud
• Amazon
• Life Sciences
• AWS
• Leadership
• Enterprise

Location: New York, NY / New Jersey
Employment Type: Full-Time
Experience: 10–15 Years