Staff Data Engineer (all genders)

As a Staff Data Engineer at Holidu, you shape a scalable data platform end-to-end, from ingestion to serving analytics-ready datasets. You’ll work closely with BI, analytics, and data science to drive high-quality data products and cost-aware, performant pipelines in a modern AWS-centric stack. You’ll lead technical direction, mentor engineers, and help recruit, all while delivering impactful insights for millions of users. Join a fast-growing, international team building data-driven travel experiences.

• travel benefits
• gym discounts
• hybrid work setup
• up to 8 weeks remote per year
• international, diverse team
• growth and AI-focused learning budgets

• Design, build, and operate end-to-end data pipelines for diverse sources (batch and streaming) to production-ready datasets
• Shape the data platform architecture and the AWS bill to balance quality, SLAs, and cost
• Develop tooling and best practices for cross-team data quality and self-service dataset construction
• Own architecture decisions and set engineering objectives in collaboration with managers
• Mentor engineers, share knowledge, and support recruitment
• Operate and monitor data infrastructure and pipelines for reliability and observability
• Collaborate with analytics and data science teams to enable decision-making at scale
• Incorporate governance and explore AI/LLM-enabled productivity improvements

• ≥8 years in Data/Software Engineering, senior or staff level experience
• Experience with Lakehouse architectures on AWS or equivalent
• Proven ability to build batch and streaming pipelines (Airflow, dbt, Redshift, Athena/Presto, Firehose, Spark, SQL databases)
• Strong Python and SQL skills; Java/Kotlin a plus
• Distributed systems knowledge and DataOps: IaC, CI/CD for data, testing, monitoring, data quality
• Containerization/orchestration (Docker, Kubernetes/EKS)
• Excellent communication; ability to influence technical direction
• Experience with Data Governance; interest in AI tooling and productivity

• effective communication
• influencing technical direction
• collaboration across disciplines
• Airflow
• dbt-core
• Redshift