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