Lead Product AI Data Engineer

About the role

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 is intended for highly experienced data engineers with deep expertise in data architecture, dimensional data modeling, analytics architecture, and AI-ready data pipelines.

What you’ll do

• Own and evolve product-level data architecture, ensuring scalability, reliability, and alignment with analytics and AI/ML use cases.
• Design and implement scalable, reliable data pipelines supporting product analytics, user behavior tracking, and AI/ML initiatives.
• Define and maintain enterprise-aligned dimensional data models (star and snowflake schemas).
• Design and maintain fact and dimension tables, ensuring correct grain, performance, and consistency.
• Contribute to and help enforce data architecture, modeling standards, naming conventions, and ETL/ELT best practices within product teams.
• Provide architectural guidance to ensure data solutions align with product requirements, platform constraints, and AI/ML needs.
• Partner with Product Managers, Data Scientists, Analysts, and Engineers to translate requirements into well-architected data models and pipelines.
• Prepare, validate, and document datasets used for analytics, experimentation, and machine learning.
• Support and evolve product event tracking architectures, ensuring alignment with dimensional models and downstream analytics.
• Implement monitoring, testing, and alerting for data quality, pipeline health, and freshness.
• Ensure integrity of fact and dimension data through validation, reconciliation, and automated checks.
• Diagnose and resolve complex data issues affecting analytics, AI workflows, or product features.
• Mentor and support data engineers through architecture reviews, code reviews, and design discussions.
• Participate in cross-team data architecture, modeling, and pipeline design reviews.
• Collaborate with platform, cloud, and security teams to ensure scalable, secure, and production-ready data architectures.

What you’ll bring

• Bachelor’s degree in engineering or master’s degree (BE, ME, B Tech, MTech, MCA, MS)
• 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
• Ability to influence technical outcomes through architectural leadership and collaboration

Nice to have

• Experience with cloud data warehouses such as Snowflake, Data Bricks
• Strong programming experience in Python for data pipelines and automation
• 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

Skills

Education

Bachelor