Senior Product AI Data Engineer

Clarivate; India; Hybrid; INR 1,500,000 - 3,000,000; Full time

Job summary

Clarivate is seeking a Senior Product AI Data Engineer/Architect to build enterprise-grade AI-ready data platforms for the Life Sciences and Healthcare ecosystem. This full-time role involves defining scalable data architectures and delivering efficient ETL/ELT pipelines to support analytics and AI initiatives.

The ideal candidate brings over five years in data engineering, proficiency in SQL and Python, and experience with cloud solutions like Snowflake and Databricks. This position operates in a hybrid model across India and the U.S.

Qualifications

• Proven experience in enterprise-scale data architecture and distributed pipeline design.
• Strong hands-on experience in Python for pipeline automation and data framework development.
• Exposure to cloud data warehouses and modern data orchestration tools.

Responsibilities

• Define and evolve enterprise-level product data architecture across multiple product lines.
• Architect scalable ETL/ELT pipelines and distributed data workflows for analytics and AI.
• Curate and validate datasets for machine learning and advanced analytics.

Skills

Data Engineering

SQL

Python

ETL/ELT Pipelines

Data Architecture

Education

5+ years of professional experience in Data Engineering or Data Architecture

Tools

Snowflake

Databricks

BigQuery

Power BI

Tableau

dbt

Airflow

Job description

Position Summary

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.

Key Responsibilities

• 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.
• 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.
• 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.

About the Team

We are part of Clarivate’s Life Sciences & Healthcare (LSH) Commercial Technology organization, working at the intersection of GenAI, applied AI, data, and product enablement. The team focuses on translating advanced AI capabilities into enterprise‑ready SaaS applications that support data‑ and workflow‑intensive products used by global pharma, biotech, and healthcare customers. The team is globally distributed across India and the U.S., operating in a hybrid model.

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.