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.
Hours of Work
Full-time, IST
40 hours per week
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.
Skills Required
- 5+ years in Data Engineering, Analytics Engineering, or Data Architecture
- Enterprise-scale data architecture and distributed pipeline design experience
- Expert-level proficiency in SQL and relational database design
- Strong hands-on experience in Python for pipeline automation and data framework development
- Deep expertise in dimensional modeling (star/snowflake schemas, fact/dimension tables, SCDs, surrogate keys, hierarchical dimensions)
- Experience designing and operating production-grade ETL/ELT pipelines for analytics and AI/ML workloads
- Experience with cloud data warehouses: Snowflake, Databricks, BigQuery
- Familiarity with 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 cloud platforms: AWS, Azure, or GCP, including governance and security
- Background in Life Sciences or Healthcare analytics
Clarivate Analytics Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Clarivate Analytics and has not been reviewed or approved by Clarivate Analytics.
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Strong & Reliable Incentives — Incentives in sales and select product/tech roles provide meaningful upside for high performers, with commission structures boosting total compensation when targets are exceeded. Role-linked variable pay is a clear strength in revenue-driving positions.
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Leave & Time Off Breadth — PTO is ample in the U.S., with paid parental leave available, making time-off policies a notable part of the package. Generous vacation and holiday allowances stand out as positives.
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Wellbeing & Lifestyle Benefits — Hybrid and remote options are common and paired with a formal wellbeing framework and EAP, supporting work–life balance. Core medical, dental, and vision coverage is broadly available in the U.S., reinforcing everyday wellbeing support.
Clarivate Analytics Insights
What We Do
Clarivate™ is a global leader in providing solutions to accelerate the lifecycle of innovation. Our bold mission is to help customers solve some of the world’s most complex problems by providing actionable information and insights that reduce the time from new ideas to life-changing inventions in the areas of science and intellectual property. We help customers discover, protect and commercialize their inventions using our trusted subscription and technology-based solutions coupled with deep domain expertise. For more information, please visit clarivate.com.
