Data Engineer II

Expedia Expedia · Hospitality · Bangalore, India

Data Engineer II role focused on building and maintaining data pipelines, ETL/ELT processes, and data models to support analytics, reporting, and data-driven product features. The role involves collaborating with cross-functional teams, optimizing data workflows, and ensuring data quality, security, and compliance. While the role mentions integrating AI/ML enabled solutions, its core focus is on data engineering infrastructure and processes.

What you'd actually do

  1. Design, build, and maintain reliable, high-quality data pipelines and ETL/ELT processes that enable analytics, reporting, and data-driven product features across multiple domains.
  2. Implement scalable data models, storage patterns, and APIs that support batch and streaming workloads while ensuring data quality, accuracy, and consistency.
  3. Collaborate with software engineers, data scientists, and product teams to understand data needs, translate requirements into technical solutions, and deliver well-documented, reusable datasets.
  4. Develop, optimize, and monitor data workflows and jobs for performance, cost efficiency, and operational robustness, including alerting, logging, and failure recovery.
  5. Apply and extend standard data engineering practices for security, privacy, governance, and compliance, including metadata management, lineage, and access control.

Skills

Required

  • Scala
  • Java
  • Python
  • Spark
  • Airflow
  • AWS Data Stack
  • SQL
  • production-grade data pipelines
  • data models
  • data services
  • monitoring
  • troubleshooting
  • reliability
  • performance

Nice to have

  • designing and optimizing large-scale data pipelines
  • data modelling
  • partitioning
  • performance tuning
  • distributed data processing
  • storage
  • streaming technologies
  • real-time and batch data products
  • improving data quality
  • observability
  • governance through automation
  • standards
  • tooling
  • AI-driven systems
  • AI/ML concepts
  • safely integrating data for AI/ML enabled solutions

What the JD emphasized

  • Scala/Java ( Must have )
  • AI/MLenabled solutions