We are hiring a Principal Product AI Data Engineer & Architect to own the design and evolution of the data foundations that power our next-generation AI products across LS&H. In this role, you will architect enterprise-scale, AI-ready data platforms that underpin drug discovery, Real-World Evidence (RWE), patient journey intelligence, market access analytics, and Generative AI / Agentic AI capabilities.
Clarivate is a global leader in connecting people and organizations to intelligence they can trust to transform their world. Our Life Sciences & Healthcare (LS&H) division powers pharmaceutical research, real-world evidence, clinical insights, and healthcare innovation for the world's leading life sciences organizations. We are on a mission to accelerate scientific discovery and improve patient outcomes through AI-driven data platforms and intelligent products.
You will partner closely with Product Managers, Software Engineers, Data Scientists, and Platform leaders across the US, Canada, and India to shape trusted, scalable, and forward-looking data solutions that directly influence product direction and AI readiness.
This is a hands-on architect role for a senior technologist who thrives at the intersection of data engineering, AI/ML enablement, and product-driven outcomes.
About You – experience, education, skills, and accomplishments
- Bachelor's Degree or equivalent in Computer Science, Data Engineering, Data Science, or related field.
- Minimum 10+ years of relevant experience in enterprise data engineering, data architecture, or AI data platforms, including significant hands-on architectural leadership.
- Deep expertise in Enterprise Data Architecture, Dimensional Data Modeling, and modern Data Pipeline Design (ETL/ELT).
- Strong hands-on experience with Databricks and modern Lakehouse architectures (Delta Lake, Unity Catalog, or equivalents).
- Proven experience designing Cloud Data Platforms at scale (AWS, Azure, or GCP) and scalable analytics ecosystems.
- Strong SQL, Python, and data modeling fundamentals.
- Demonstrated ability to lead cross-team architectural decisions and influence senior technical and product stakeholders.
It would be great if you also
- Experience in Life Sciences, Healthcare, Pharma, or Real-World Evidence (RWE) domains.
- Familiarity with vector databases, embeddings, LLM orchestration frameworks (LangChain, LlamaIndex, or similar), and evaluation frameworks.
- Exposure to healthcare data standards (HL7, FHIR, OMOP, claims data) is a strong plus.
- Experience partnering with globally distributed teams across US, Canada, and India.
What will you be doing in this role
Architecture & Technical Leadership
- Own the end-to-end architecture of scalable data pipelines, lakehouse platforms, and AI-ready datasets supporting product analytics, experimentation, and AI/GenAI use cases.
- Design and oversee analytics- and AI-ready data models (dimensional, semantic, feature stores) that ensure consistency, reuse, and performance across product domains.
- Lead the design of modern data platforms leveraging Databricks, Delta Lake, and Lakehouse architectures, with strong governance and observability built in.
- Architect data flows end to end — from event generation, ingestion, and transformation through analytics and downstream AI/ML consumption (RAG, Agentic AI, LLM-powered features).
AI & GenAI Enablement
- Define and evolve the data foundations required for GenAI, RAG pipelines, Agentic AI workflows, and MLOps at enterprise scale.
- Partner with Data Science and AI Engineering teams to enable feature engineering, vector stores, embeddings, and model-ready datasets.
- Establish AI SDLC standards spanning data quality, lineage, evaluation, and responsible AI practices.
Data Quality, Governance & Reliability
- Analyze data quality, pipeline health, and usage patterns; lead resolution of complex issues impacting product insights and AI model performance.
- Audit data pipelines, transformations, and datasets to ensure accuracy, security, compliance (HIPAA, GDPR where applicable), and adherence to enterprise standards.
- Contribute to and uphold data engineering standards, documentation, and best practices across teams.
Partnership & Influence
- Partner closely with Product Managers, Software Engineers, Data Analysts, and Data Scientists to shape data solutions that deliver measurable product and business impact.
- Advise senior engineers and architects on scope, tradeoffs, sequencing, and implementation options.
- Influence and mentor senior and principal engineers through architecture reviews, design guidance, and technical thought leadership.
About the Team
The DIA team operates globally and collaborates closely with product owners, architects, and data experts. We thrive on innovation, diversity, and a mission-driven culture focused on enabling life-changing insights.
Team comprising front-end and back-end engineers, QA, UX designers, product managers, and DevOps specialists. The team is focused on delivering high-quality editorial and data intelligence solutions, with a strong emphasis on innovation, ownership, and cross-functional collaboration.
This is a fast-paced, innovation-driven environment where you’ll have the opportunity to take ownership of features, contribute to system design, and collaborate with talented peers on impactful projects.
Hours of Work
- Hybrid working environment
At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.
