Senior AI/ML Data Engineer - Trusted Data Pipelines

Expedia; United States; On-site; USD 140,000 - 200,000; Full time

Job summary

Expedia Group's Layla team is seeking a Senior AI/ML Data Engineer to build the data foundations powering AI-native travel planning. You will design reliable, scalable data pipelines across Layla and related systems, ensure data quality, and enable experimentation and model evaluation in production.

You will collaborate with Product, Analytics, and ML/engineering teams to turn questions into trusted data, mentor peers, and promote engineering excellence in data.

Qualifications

• 8+ years of relevant professional experience.
• Bachelor's degree required or equivalent professional experience.
• Strong SQL, data modeling, and Python for data engineering.
• Experience designing and operating production data pipelines.
• Familiarity with AI/ML systems production workflows and evaluation datasets.

Responsibilities

• Design, build, and operate scalable data pipelines powering Layla's AI-native experiences.
• Own data quality, reliability, and observability for critical datasets.
• Build data foundations for experimentation and model evaluation.
• Enable production use of AI/ML systems with feature pipelines and monitoring.
• Collaborate with Product, Analytics, and ML/engineering teams to derive reliable data insights.
• Mentor engineers on best practices for data engineering.

Skills

Advanced SQL

Data modeling

Python

Data pipelines

Data quality

Observability

AI/ML in production

Education

Bachelor's degree in Computer Science, Data Engineering, or related field

Tools

dbt

BigQuery or Snowflake

Looker/Metabase

Job description

Expedia Group's Layla team is seeking a Senior AI/ML Data Engineer to build the data foundations powering AI-native travel planning. You will design reliable, scalable data pipelines across Layla and related systems, ensure data quality, and enable experimentation and model evaluation in production.

You will collaborate with Product, Analytics, and ML/engineering teams to turn questions into trusted data, mentor peers, and promote engineering excellence in data.