Data Engineer (Restaurant AI CoPilot)

• As a Data Engineer on the Data Science team at OpenTable, you will design, build, and maintain robust data solutions that power diner features, partner integrations, and advanced AI initiatives
• You will work closely with cross-functional teams including Product Managers, Business Intelligence Analysts, Infrastructure SREs, and Product Engineers to deliver scalable data products
• Joining a agile, high-impact team, you will leverage OpenTable's vast data ecosystem to drive key business decisions and enhance user experiences globally
• Design, test, deploy, and maintain scalable batch and streaming data pipelines to deliver reliable data to internal and external customers
• Collaborate with Product Managers, Business Intelligence Analysts, SREs, and Product Engineers to architect and govern production data services
• Build data pipelines providing actionable insights to restaurants regarding guest behaviour, revenue, and operational efficiency
• Develop and maintain data integrations with external partners to support critical business partnerships and data exchange
• Power diner analytics and machine learning work streams for Sales, Marketing, and AI initiatives, including generative AI content summarization
• Monitor and optimize production systems to ensure high performance, data availability, and system integrity

Benefits

• Generous parental leave
• Generous paid vacation + time off for your birthday
• Paid volunteer time
• Enriched learning and development opportunities - leadership development & access to thousands of on-demand e-learnings
• Work from (almost) anywhere - wherever you do your best work
• Mental health and well-being - company-paid therapy sessions through SpringHealth, company-paid subscription to HeadSpace, and company-wide weeks off a year so the whole team can recharge

Experience working in cross-functional environments and collaborating with product and technical stakeholders

Demonstrated professional experience in data engineering principles, data architecture, and software design

Experience constructing scalable batch and streaming data pipelines

Proficiency in Python, SQL, and at least one strongly typed language (such as Java)

Proven track record of building, testing, deploying, monitoring, and maintaining production data systems

Experience with data engineering stack components such as PySpark, Databricks, Snowflake, Airflow, Kubernetes, and AWS

Knowledge or experience in Machine Learning development (e.g., NLP, LLMs, RAG, recommendations, or MLOps)

Familiarity with containerization, orchestration, and monitoring tools like Docker, Kubernetes, Helm, Prometheus, or Grafana

Familiarity with data storage and infrastructure solutions such as Kafka, Snowflake, Delta Lake, or vector/NoSQL databases

Understanding of A/B testing best practices and data-driven product evaluation