The ad says“Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability”
The ad says“Strong analytical and troubleshooting skills for investigating data issues”
The ad says“Modern BI tooling (e.g., Looker, Superset)”
The ad says“CI/CD and deployment automation (e.g., GitHub Actions)”
The ad says“Experience with workflow orchestration and containerization (examples: Airflow, Docker)”
The ad says“Experience owning end-to-end data pipelines (ingest → transform → test → monitor)”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Web frameworks for internal tools (e.g., Django, Flask)”
The ad says“Experience with workflow orchestration and containerization (examples: Airflow, Docker)”
The ad says“Web frameworks for internal tools (e.g., Django, Flask)”
The ad says“Stream processing or real-time systems (e.g., Kafka, Flink)”
The ad says“CI/CD and deployment automation (e.g., GitHub Actions)”
The ad says“Stream processing or real-time systems (e.g., Kafka, Flink)”
The ad says“Modern BI tooling (e.g., Looker, Superset)”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability”
The ad says“Proficiency in Python and a software-engineering approach to building testable, maintainable code”
The ad says“Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability”
The ad says“Stream processing or real-time systems (e.g., Kafka, Flink)”
The ad says“Modern BI tooling (e.g., Looker, Superset)”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Strong analytical and troubleshooting skills for investigating data issues”
The ad says“Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)”
The ad says“Web frameworks for internal tools (e.g., Django, Flask)”
The ad says“Experience with workflow orchestration and containerization (examples: Airflow, Docker)”
We are looking for a Senior Data Engineer to join our Business Intelligence team
Our team builds and operates the data backbone that serves as the single source of truth for the organization. We manage KAYAK’s business-critical reporting to support billing and provide the foundation for company-wide reporting and analytics
If you want to build the systems that define how the business measures success, we’d love to hear from you
Architect for scale: Develop and monitor robust data pipelines using Python, SQL, and Rundeck/Airflow that handle large-scale data volumes with high reliability
Optimize performance: Design performant data models and optimize complex SQL queries for high-scale environments
Ensure data reliability: build automated checks and alerts to catch errors early so financial and operational reports remain accurate
Increase data access: automate repetitive tasks and build self-service tools to make data easier to use across teams
Drive engineering excellence: experiment with and leverage AI-assisted coding tools to accelerate development cycles and enhance code quality
Work with partners across the company: translate business questions into practical, maintainable technical solutions
Benefits
Work flexibly: Our global flexible work policy lets our teams decide if they head into one of our offices or work from anywhere else
Team-wide time off: Most of our team disconnects at the same time each year to recharge and reconnect
Global volunteer week: Take VTO (Volunteer Time Off) to support the organizations and charitable efforts you believe in
Wellness: We take care of each other - providing opportunities and spaces to live that work-life balance
Resource groups: Our five ERGs are employee-led groups for underrepresented communities and their allies
Career growth: We provide opportunities for our team to develop their skills – or learn new ones – on their own terms
Preferred experience
Strong analytical and troubleshooting skills for investigating data issues
5+ years of proven experience in data engineering or analytics engineering within a related data-centric environment
Experience with workflow orchestration and containerization (examples: Airflow, Docker)
Strong SQL skills and familiarity with distributed/columnar/OLAP systems (examples: Redshift, Trino, Vertica) and relational databases (e.g., MySQL, Postgres)
Experience owning end-to-end data pipelines (ingest → transform → test → monitor)
Proficiency in Python and a software-engineering approach to building testable, maintainable code
Strong written and spoken English to communicate effectively across teams
Stream processing or real-time systems (e.g., Kafka, Flink)
Modern BI tooling (e.g., Looker, Superset)
CI/CD and deployment automation (e.g., GitHub Actions)
Web frameworks for internal tools (e.g., Django, Flask)
