Senior/Lead Product Data Engineer

Role Overview:

As a Senior Lead Product AI Data Engineer, you will be responsible for designing, building, and optimizing end-to-end data architecture and scalable data platforms that power product analytics and AI-driven capabilities. This role is ideal for highly experienced data engineers with over 7 years of experience and expertise in data architecture, dimensional data modeling, analytics architecture, and AI-ready data pipelines. Operating as a senior individual contributor and technical lead, you will own product-level data architecture decisions, complex data models, and pipelines while influencing technical direction through hands-on leadership and mentorship. Collaborating closely with Product Managers, Data Scientists, Analysts, and Platform Engineers, you will ensure that product and AI data are accurate, well-architected, scalable, and analytics-ready. This role involves blending data architecture ownership, deep technical execution, dimensional modeling excellence, and team-level technical leadership.

Key Responsibilities:

• 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.

Qualifications Required:

• Bachelor's degree in engineering or master's degree (BE, ME, B Tech, MTech, MCA, MS).
• Minimum 7+ years of professional experience in data engineering, analytics engineering, or data architecture-heavy roles.
• Expert-level proficiency in SQL and relational database design.
• Strong programming experience in Python for data pipelines and automation.
• 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.

Additional Details:

The team operates globally and collaborates closely with product owners, architects, and data experts, focusing on innovation, diversity, and a mission-driven culture. The team comprises front-end and back-end engineers, QA, UX designers, product managers, and DevOps specialists, delivering high-quality editorial and data intelligence solutions with a strong emphasis on innovation, ownership, and cross-functional collaboration. This fast-paced, innovation-driven environment offers the opportunity to take ownership of features, contribute to system design, and collaborate with talented peers on impactful projects. Role Overview:

As a Senior Lead Product AI Data Engineer, you will be responsible for designing, building, and optimizing end-to-end data architecture and scalable data platforms that power product analytics and AI-driven capabilities. This role is ideal for highly experienced data engineers with over 7 years of experience and expertise in data architecture, dimensional data modeling, analytics architecture, and AI-ready data pipelines. Operating as a senior individual contributor and technical lead, you will own product-level data architecture decisions, complex data models, and pipelines while influencing technical direction through hands-on leadership and mentorship. Collaborating closely with Product