Technical Life Sciences Consultant - Databricks & Commercial Pharma
Job Description
About the Role
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We are seeking a Technical Life Sciences Consultant to help drive AI-led business transformation for a leading pharmaceutical client in Princeton, NJ.
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This role combines life sciences consulting, data architecture, Databricks, AWS, and AI/data modernization. You will work closely with senior business and technology stakeholders, data product owners, architects, and engineering teams to design and deliver scalable, secure, and cost-effective data and AI platforms.
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The ideal candidate brings strong commercial pharma domain expertise, hands-on experience with Databricks and modern data engineering, and the consulting presence to lead client conversations and translate complex business requirements into scalable technology solutions.
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Key Responsibilities
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Client & Technical Leadership
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- Lead client workshops focused on problem framing, solution design, and technical strategy.
- Partner with business and technology stakeholders to translate requirements into scalable data and AI architectures.
- Provide end-to-end technical advisory across complex transformation programs.
- Present architecture recommendations and technical roadmaps to senior client stakeholders.
- Support RFP/RFI responses, solution proposals, and technical evaluations.
- Identify opportunities for modernization, platform adoption, and new AI/data capabilities.
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Data & AI Architecture
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- Design and guide implementation of modern, cloud-native data platforms using AWS and Databricks.
- Develop scalable architectures supporting analytical, operational, and AI/ML workloads.
- Define data models, data pipelines, consumption layers, and platform patterns.
- Translate complex analytical requirements into scalable data architectures.
- Assess current-state environments and define future-state data and AI platform architectures.
- Establish architectural standards and reusable patterns for scalability, performance, security, and cost optimization.
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Databricks & Data Engineering
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- Architect solutions using Databricks, Apache Spark, Python, and SQL.
- Work with distributed compute and modern data processing paradigms.
- Design data ingestion, transformation, orchestration, and consumption frameworks.
- Apply modern data modeling approaches, including Data Vault 2.0 where appropriate.
- Collaborate with engineering teams on implementation, optimization, and technical execution.
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AI Foundations & Data Governance
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- Help establish foundational capabilities required for enterprise AI adoption.
- Define standards for metadata, lineage, data quality, data modeling, and governance.
- Support operational, context, and ontology layers within modern AI/data platforms.
- Establish frameworks for observability, monitoring, reliability, and operational excellence.
- Drive adoption of enterprise data platforms and modern data engineering practices.
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Required Qualifications
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- 10+ years of experience in AI, software development, data engineering, data architecture, or related fields.
- 5+ years of life sciences/pharmaceutical consulting experience, preferably with commercial pharma.
- Strong experience with Databricks and modern data platform architecture.
- Strong hands-on knowledge of Python, Spark, and SQL.
- Experience with AWS data and cloud services.
- Strong understanding of distributed computing, cloud-native architectures, and modern data engineering patterns.
- Experience with data modeling and Data Vault 2.0; exposure to automate_dv is a plus.
- Experience designing and implementing scalable data pipelines and analytical platforms.
- Understanding of data governance, metadata, lineage, data quality, and security.
- Experience with CI/CD, DevOps, testing, monitoring, and observability.
- Strong communication and stakeholder management skills.
- Ability to operate effectively across multi-team onsite/offshore delivery models.
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Preferred Qualifications
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- Experience building AI foundations or enterprise AI platforms within pharmaceutical organizations.
- Experience with commercial pharma datasets and use cases.
- Experience with data modernization and cloud migration programs.
- Experience with AWS services including S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis.
- Experience with dbt Core or dbt Cloud.
- Experience designing self-service analytics and data products.
- Strong executive presence and experience working with VP/Executive Director-level stakeholders.
- Experience leading technical workshops, architecture reviews, and transformation roadmaps.
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What You'll Bring
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We are looking for someone who can operate at the intersection of technology, data, AI, and business. You should be comfortable moving from an executive-level business discussion to an architecture whiteboard and then working with engineering teams to ensure the solution is successfully delivered.
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You will have the opportunity to shape modern AI and data foundations for a leading pharmaceutical organization while working on large-scale cloud and Databricks transformation initiatives.