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 engineeringProven experience leading multiple engineering teams and managers in a product-centric environmentStrong background in product engineering, including building and operating customer-facing or platform product systemsDeep expertise in SQL and relational data conceptsHands-on experience with Python for data pipelines, automation, or data validation frameworksAdvanced expertise in dimensional data modeling, including:Fact and dimension table designStar and snowflake schemasConformed dimensions and shared metricsProven experience designing and operating slowly changing dimensions (SCDs), surrogate keys, and data grain strategiesTrack record delivering enterprise-scale, well-modeled analytical and AI data platformsExceptional leadership, executive stakeholder management, and communication skillsIt would be great if you also had . . .
Experience with cloud data warehouses such as Snowflake, BigQuery, Databricks, or Amazon RedshiftFamiliarity 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 practicesWhat would you be doing in this role:
Product-aligned, scalable data and AI platforms built on strong dimensional data modeling foundationsHigh-quality, well-modeled fact and dimension datasets trusted by engineering, product, analytics, and AI teamsReliable, observable, and governed data systems supporting customer-facing and regulated environmentsHigh-performing, product-driven engineering organizations accelerating AI-led innovation and scientific discoveryOrganizational & People Leadership
Lead, mentor, and scale multiple teams spanning product-focused data engineers, analytics engineers, and software engineering managersDefine org design, career frameworks, performance expectations, and succession planning across product-aligned teamsBuild a strong engineering culture emphasizing product ownership, data modeling rigor, quality, reliability, and continuous improvementDrive strategic hiring and workforce planning aligned with product roadmaps and AI initiativesStrategic Delivery & Execution
Own end-to-end delivery of product analytics, AI data, and dimensional data platform initiatives across multiple product areasTranslate product, AI, and engineering strategy into multi-year data architecture and modeling roadmapsBalance customer-facing product enablement, platform scalability, reliability, and technical debt reductionEnsure predictable delivery, operational excellence, and strong cross-functional execution with product engineering teamsTechnical Leadership & Architecture Oversight
Provide executive technical leadership for product data pipelines, ETL/ELT workflows, real-time data flows, and AI data foundationsEstablish and enforce enterprise dimensional data modeling standards, including:Fact and dimension table designStar and snowflake schemasConformed dimensions and shared metricsGuide 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 domainsPartner with Principal and Senior Principal Engineers to define long-term product data, analytics, and AI platform architectureProduct, Analytics & AI Enablement
Collaborate deeply with Product Management and Product Engineering to embed well-modeled data into product design and deliveryEnsure product event instrumentation and telemetry align to clear fact tables and dimensional structures supporting experimentation and AIEnable AI-powered product experiences by overseeing clean, historical, and well-grained dimensional datasets for model training, inference, and feedback loopsChampion self-service analytics and AI enablement through trusted, documented, and semantically consistent data productsData Quality, Reliability & Governance
Establish enterprise-wide standards for data quality, testing, observability, and reliability, with dimensional modeling as a foundationEnsure monitoring, alerting, and incident response processes protect critical fact tables, dimensions, and downstream metricsLead resolution of complex, cross-domain data issues impacting customer-facing features, analytical correctness, or AI outcomesPartner with security, privacy, and compliance teams to ensure responsible use of product data, lineage, and access controlsAbout 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-timeHybrid working modelLocation: BengaluruAt 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.