You will own the data product strategy, dimensional data architecture, engineering standards, platform design and AI roadmap, ensuring our data products are trusted, performant, discoverable, and monetizable.
About You – Experience, Skills & Accomplishments
Minimum 15+ years in data engineering, software engineering, analytics, or data product leadership, including 4+ years managing managers and global teams
Proven success building and scaling enterprise-grade data products using software engineering and data modeling best practices
Deep experience embedding AI, ML, and GenAI into data-centric and analytics-driven products
Strong data modeling expertise:
Dimensional modeling (facts & dimensions)
Star and snowflake schema design
Conformed dimensions and analytical data models
Modeling for BI, analytics, and AI/ML workloads
Experience creating domain-oriented data models, semantic layers, and metrics frameworks
Hands-on or architectural experience with cloud-native development (AWS, Azure, or GCP) and data platform engineering
Proficiency in Python, Java, SQL, microservices, and data-centric application development
Good knowledge of AWS services (EC2, Lambda, S3, RDS), Docker, Kubernetes, and CI/CD for data/AI workloads
Expertise with modern data platforms (Snowflake, Databricks, lakehouse architectures, Spark, and streaming frameworks )
Background in AI/ML frameworks (TensorFlow, PyTorch), MLOps, feature stores, and model lifecycle management will be a plus
Experience with Generative AI, LLMs, RAG architectures, agentic systems, and MCP (Model Context Protocol) a strong plus
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
Bonus Points
Experience delivering commercial data-as-a-product or analytics offerings
Familiarity with Life Sciences/Healthcare domains (RWE, clinical, or commercial data models)
Strong passion for customer outcomes, product thinking, and measurable business impact
What You Will Be Doing
Data Product, Analytics & AI Strategy
Lead and scale a global organization of 30+ engineers delivering large-scale, mission-critical data products trusted by top 20 global pharmaceutical companies
Define and drive the data product, analytics, and AI roadmap across the LSH portfolio
Partner with product and business leaders to design analytics-ready, customer-centric data products
Establish data product ownership, SLAs, quality KPIs, and lifecycle management
Ensure governance, privacy, and compliance are embedded by design
Software Engineering & Data Modeling
Lead the design and delivery of software‑engineered, modular, API-first data products
Own enterprise analytical data models, including dimensional models, star/snowflake schemas, conformed dimensions, and reusable metrics
Ensure data models support high‑performance analytics, BI, ML, and GenAI use cases
Champion engineering excellence: test automation, CI/CD, observability, data quality, performance optimization
Data Platform & Analytics Engineering
Own cloud data platform architecture—lakehouse, streaming, and real-time analytics capabilities
Enable semantic modeling, analytics engineering, and self-service BI through trusted dimensional models
Define standards for data quality, lineage, metadata, discoverability, and metric consistency
Optimize models for scalability, cost efficiency, and performance
AI, GenAI & Intelligent Data Products
Lead development of AI-powered data products—predictive analytics, GenAI, and LLM-based experiences
Drive MLOps and LLMOps to operationalize AI at scale
Explore advanced capabilities such as metrics-aware LLMs, semantic search over dimensional models, and agentic analytics
Leadership & Team Development
Build, mentor, and grow a high-impact global team across data modeling, data engineering, ML engineering, and platform engineering
Foster a data-model-driven, product-centric, engineering-first culture
Lead hiring, talent development, and performance management
Collaboration & Influence
Partner with product, data science, BI, and business leaders to align metrics, dimensions, and analytical logic
Communicate data product strategy, modeling decisions, and AI outcomes to senior executives
About the Team
You will join the Life Sciences & Healthcare Commercial Product Engineering organization, leading a globally distributed team across India and the United States focused on delivering high-quality, AI-powered, well-modeled data products at scale.
Hours of work
Full-time
Hybrid working model
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
- Minimum 15+ years in data engineering or software engineering
- 4+ years managing managers and global teams
- Proven success building enterprise-grade data products
- Deep experience embedding AI and ML into products
- Hands-on experience with cloud-native development
- Proficiency in Python, Java, SQL, and microservices
- Good knowledge of AWS services
- Expertise with modern data platforms like Snowflake
- Background in AI/ML frameworks like TensorFlow
- Familiarity with Life Sciences/Healthcare domains
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.
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