Yotpo is leading the next era of trust and loyalty in eCommerce. With AI-powered Reviews and Loyalty solutions, we help brands turn browsers into customers and customers into advocates. Through deep integrations across the eCommerce ecosystem and the trust of over 30,000 global brands, Yotpo delivers seamless omnichannel experiences that increase conversion, strengthen customer relationships, and drive profitable, long-term growth.

About the Role

Are you an experienced Data Engineer ready to build the data foundation for the next wave of eCommerce discovery?

Join Yotpo’s high-impact Discover R&D team, where we are revolutionizing how brands and products are found in the AI era. The future of eCommerce, shaped by Large Language Models (LLMs), is already visible in how consumers use tools like ChatGPT or Perplexity for shopping questions. Yotpo Discover is leading the mission to ensure brands remain visible, trusted, and cited in this new, AI-driven world.

Operating like an internal startup, our team is fast-paced, hands-on, and driven by curiosity. We rapidly experiment, build, and launch new AI-powered products that redefine brand-shopper connections in the age of conversational search.

As we explore this emerging domain, we’re looking for talented builders who thrive at the intersection of AI, Big Data, and experimentation.

Responsibilities

Architect Discovery Pipelines: Design and maintain high-throughput, low-latency data pipelines that process billions of events, ensuring reviews and visual UGC are instantly discoverable across channels.
Data Modeling for AI/Search: Build and optimize complex data models that support advanced search algorithms, LLM-based product summaries, and personalized shopper experiences.
Bridge Engineering & Data Science: Partner with AI Researchers to operationalize machine learning models that calculate “convertibility” and product relevance in real-time.
Scale for Growth: Own the end-to-end lifecycle of our data stack, ensuring it can handle the next 10x of business growth while maintaining strict reliability and observability.
Independent Impact: Lead technical initiatives from ideation to production, balancing the rapid experimentation needs of the Discover product with the stability of a core R&D system.
Promote Best Practices: Drive the evolution of our modern data stack (DBT, Databricks) by implementing “standards-as-code” and automated quality gates.

Requirements

Education: Bachelor’s degree in Computer Science, Mathematics, Industrial Engineering, or an equivalent analytical discipline.
Experience: 4+ years of hands-on experience as a Data Engineer or Backend Engineer with a strong data focus.
SQL Mastery: Advanced proficiency in SQL and deep understanding of modern data warehousing (Databricks, Snowflake, BigQuery, or Redshift).
Architecture & Modeling: Proven experience in designing data architectures for complex business domains, specifically those involving high-velocity event streaming or large-scale content indexing.
Ownership Mentality: A “builder” mindset with the ability to work independently in a fast-paced, startup-like environment within a global company.

Nice to Have (Strong Advantage)

DBT Expert: Extensive experience with DBT (Data Build Tool) for modular data modeling.
Python & Orchestration: Strong Python skills and experience with workflow tools (e.g., Airflow, Dagster).
AI/LLM Interest: Familiarity with integrating AI/LLM technologies (OpenAI, Anthropic) or vector databases.
Big Data Stack: Experience with Spark, Databricks, Kubernetes, and Docker.

BI & Visualization: Experience with Looker, Tableau, or Superset to help product analysts “discover” insights within our own data.

#LI-Hybrid