Lead Product AI Data Engineer; Bangalore, India

We are seeking a Lead 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** * 10+ 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 **What will you be doing in this role:** * 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 **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 **AI & Product Data Enablement** * 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.