Job Description

We are seeking a Director, Product AI Data Engineering to lead and scale multiple engineering organizations responsible for building enterprise-grade product data and AI platforms that power customer-facing features, product analytics, experimentation, and AI-driven product capabilities.


This role is designed for a senior engineering leader with 15+ years of experience across product engineering and data engineering, combining strong organizational leadership, deep technical expertise, and strategic execution. As a Director, you will own delivery outcomes across multiple product domains, shape data and AI platform strategy, and ensure data engineering investments directly enable product experiences, growth, and AI innovation.These platforms serve as the foundation for critical data products that help researchers, clinicians, scientists, and business leaders make faster, more confident decisions.


You will help build the data engine behind products used to accelerate drug discovery, evaluate treatment effectiveness, model patient journeys, and bring life-saving innovations to market. Our products are trusted by leading pharmaceutical companies, biotech innovators, medical device leaders, academic institutions, and healthcare organizations worldwide.


You will partner closely with Product Management, Product Engineering, AI/ML, Analytics, and Platform Engineering leadership to ensure data and AI foundations are scalable, well-modeled, reliable, governed, and tightly integrated into the product development lifecycle.

About You - experience, education, skills, and accomplishments

Bachelor's or master's degree in computer science, Engineering, or a related field. Minimum 15+ years of professional experience across product engineering, data engineering, or platform engineering Proven experience leading multiple engineering teams and managers in a product-centric environment Strong background in product engineering, including building and operating customer-facing or platform product systems Deep expertise in SQL and relational data concepts Hands-on experience with Python for data pipelines, automation, or data validation frameworks Advanced expertise in dimensional data modeling, including: + Fact and dimension table design
+ Star and snowflake schemas
+ Conformed dimensions and shared metrics
Proven experience designing and operating slowly changing dimensions (SCDs), surrogate keys, and data grain strategies Track record delivering enterprise-scale, well-modeled analytical and AI data platforms Exceptional leadership, executive stakeholder management, and communication skills

It would be great if you also had . . .

Experience with cloud data warehouses such as Snowflake, BigQuery, Databricks, or Amazon Redshift Familiarity with modern data and product engineering tools (e.g., dbt, Airflow, Kafka, Fivetran, Segment) Experience with event-driven, streaming, or near real-time product data (clickstream, telemetry, logs) Working knowledge of BI, experimentation, and product analytics platforms (Power BI, Tableau, Amplitude, etc.) Experience with AWS, Azure, or GCP, including data governance, security, and privacy best practices

What would you be doing in this role:

Product-aligned, scalable data and AI platforms built on strong dimensional data modeling foundations High-quality, well-modeled fact and dimension datasets trusted by engineering, product, analytics, and AI teams Reliable, observable, and governed data systems supporting customer-facing and regulated environments High-performing, product-driven engineering organizations accelerating AI-led innovation and scientific discovery

Organizational & People Leadership

Lead, mentor, and scale multiple teams spanning product-focused data engineers, analytics engineers, and software engineering managers Define org design, career frameworks, performance expectations, and succession planning across product-aligned teams Build a strong engineering culture emphasizing product ownership, data modeling rigor, quality, reliability, and continuous improvement Drive strategic hiring and workforce planning aligned with product roadmaps and AI initiatives

Strategic Delivery & Execution

Own end-to-end delivery of product analytics, AI data, and dimensional data platform initiatives across multiple product areas Translate product, AI, and engineering strategy into multi-year data architecture and modeling roadmaps Balance customer-facing product enablement, platform scalability, reliability, and technical debt reduction Ensure predictable delivery, operational excellence, and strong cross-functional execution with product engineering teams

Technical Leadership & Architecture Oversight

Provide executive technical leadership for product data pipelines, ETL/ELT workflows, real-time data flows, and AI data foundations Establish and enforce enterprise dimensional data modeling standards, including: + Fact and dimension table design
+ Star and snowflake schemas
+ Conformed dimensions and shared metrics
Guide teams on data grain definition, surrogate keys, and slowly changing dimensions (SCD Types 1, 2, and hybrid patterns) Ensure analytical and AI datasets are consistent, explainable, and reusable across products and domains Partner with Principal and Senior Principal Engineers to define long-term product data, analytics, and AI platform architecture

Product, Analytics & AI Enablement

Collaborate deeply with Product Management and Product Engineering to embed well-modeled data into product design and delivery Ensure product event instrumentation and telemetry align to clear fact tables and dimensional structures supporting experimentation and AI Enable AI-powered product experiences by overseeing clean, historical, and well-grained dimensional datasets for model training, inference, and feedback loops Champion self-service analytics and AI enablement through trusted, documented, and semantically consistent data products

Data Quality, Reliability & Governance

Establish enterprise-wide standards for data quality, testing, observability, and reliability, with dimensional modeling as a foundation Ensure monitoring, alerting, and incident response processes protect critical fact tables, dimensions, and downstream metrics Lead resolution of complex, cross-domain data issues impacting customer-facing features, analytical correctness, or AI outcomes Partner with security, privacy, and compliance teams to ensure responsible use of product data, lineage, and access controls

About the Team

You will join a highly collaborative, global product engineering organization (US , Canada and India) focused on enabling product intelligence and AI-driven insights at scale.

Hours of work

Full-time Hybrid working model Location: Bengaluru

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.