Senior Product AI Data Engineer

About the role

Proven experience in enterprise-scale data architecture and distributed pipeline design. Expert-level proficiency in SQL and relational database design. Deep expertise in dimensional modeling, including star and snowflake schemas, fact/dimension tables, SCDs, surrogate keys, and hierarchical dimensions.

What you'll do

• 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

What you need

• 5–9 yrs of experience
• Machine learning
• SQL
• Data modelling
• ETL
• Python
• Snowflake
• Any graduate

Good to have

• AWS
• LLMs
• Databricks
• BigQuery
• dbt
• Airflow