We are seeking a Lead Product AI Data Engineer / Architect to design, build, and optimize end-to-end data architecture and scalable data platforms that power product analytics and AI-driven capabilities.
This role blends data architecture ownership, deep technical execution, dimensional modeling excellence, and team-level technical leadership for AI Ready Product Data Pipelines.
About You – experience, education, skills, and accomplishments
Bachelor’s degree in engineering or master’s degree (BE, ME, B Tech, MTech, MCA, MS) with minimum 7 years professional experience in data engineering, analytics engineering, or data architecture–heavy roles.
Expert-level proficiency in SQL and relational database design.
Deep hands-on experience with data architecture and dimensional data modeling, including star schemas, snowflake schemas, fact tables, and dimension tables.
Strong understanding of slowly changing dimensions (SCDs), surrogate keys, grain definition, and hierarchical dimensions.
Experience designing and operating ETL/ELT pipelines for production analytics and AI/ML workloads.
It would be great if you also have:
Experience with cloud data warehouses such as Snowflake, Data Bricks
Strong programming experience in Python for data pipelines and automation is a big plus.
Familiarity with tools such as dbt, Airflow, Fivetran, and Segment.
Exposure to BI and visualization tools (Power BI, Tableau, SAP BusinessObjects).
Familiarity with AWS, Azure, or GCP, including data governance and security best practices.
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 and also manage Data Architecture & Technical Leadership for Product & AI Data Enablement with Data Quality, Reliability & Operations
About the Team
The DIA team operates globally and collaborates closely with product owners, architects, and data experts. We thrive on innovation, diversity, and a mission-driven culture focused on enabling life-changing insights.
Team comprising front-end and back-end engineers, QA, UX designers, product managers, and DevOps specialists. The team is focused on delivering high-quality editorial and data intelligence solutions, with a strong emphasis on innovation, ownership, and cross-functional collaboration.
This is a fast-paced, innovation-driven environment where you’ll have the opportunity to take ownership of features, contribute to system design, and collaborate with talented peers on impactful projects.
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
- Bachelor's or master's degree in engineering or related field
- Minimum 7 years of professional experience in data engineering or related roles
- Expert-level proficiency in SQL and relational database design
- Deep hands-on experience with dimensional data modeling
- Experience designing ETL/ELT pipelines
- Experience with cloud data warehouses such as Snowflake or Data Bricks
- Strong programming experience in Python
- Familiarity with BI and visualization tools
