We are seeking a Senior Product AI Data Engineer / Architect to define, build, and scale enterprise-grade AI-ready data platforms for the Life Sciences and Healthcare (LSH) ecosystem. This role combines hands-on technical mastery with enterprise architecture leadership, influencing multiple product lines and setting long-term standards for dimensional modeling, analytics pipelines, and AI data enablement.

About you education and Qualifications

• 5+ years of professional experience in Data Engineering, Analytics Engineering, or Data Architecture.

• Proven experience in enterprise-scale data architecture and distributed pipeline design. Expert-level proficiency in SQL and relational database design.

• Strong hands-on experience in Python for pipeline automation, orchestration, and data framework development.

• Deep expertise in dimensional modeling, including star and snowflake schemas, fact/dimension tables, SCDs, surrogate keys, and hierarchical dimensions.

• Experience designing and operating production-grade ETL/ELT pipelines for analytics and AI/ML workloads and strong ability to influence technical outcomes through architectural leadership and enterprise strategy.

What will you be doing in this role:

• Experience with cloud data warehouses: Snowflake, Databricks, BigQuery.

• Familiarity with modern data orchestration and transformation tools: dbt, Airflow, Fivetran, Segment.

• Experience handling semi-structured and event-driven data (JSON, logs, clickstream).

• Exposure to BI and visualization tools: Power BI, Tableau, Looker, SAP BusinessObjects.

• Experience with AWS, Azure, or GCP, including data governance, security, and compliance frameworks.

• Background in Life Sciences or Healthcare analytics.

What will you be doing in this role

• Define and evolve enterprise-level product data architecture across multiple product lines, ensuring scalability, reliability, and AI/ML readiness.

• Architect scalable ETL/ELT pipelines and distributed data workflows for analytics, AI, and product intelligence.

• Develop and enforce dimensional data modeling standards (star schemas, snowflake schemas) across the organization.

• Design and maintain fact and dimension tables, ensuring proper grain, SCD handling, hierarchical dimensions, and high-performance queries.

• Establish data architecture principles, naming conventions, and best practices for ETL/ELT, event tracking, and AI pipelines.

• Serve as the technical authority guiding architecture decisions to meet product, platform, and AI requirements

AI & Product Data Enablement

• Partner with cross-functional teams to translate requirements into highly scalable, analytics- and AI-ready data models and pipelines.

• Curate and validate datasets for machine learning, experimentation, and advanced analytics.

• Evolve event-driven architectures to align with dimensional modeling and downstream analytics.

• Establish feature store frameworks and reusable AI data pipelines across multiple products.

About the Team

You will be part of Clarivate’s Life Sciences & Healthcare (LSH) Commercial Technology organization, working at the intersection of GenAI, applied AI, data, and product enablement. The team focuses on translating advanced AI capabilities into enterprise-ready SaaS applications that support data- and workflow-intensive products used by global pharma, biotech, and healthcare customers. The team is globally distributed across India and the U.S., operating in a hybrid model.

Hours of Work

Full-time, IST

40 hours per week

Hybrid working environment