Data Engineer
Not sure if you're a good fit?
Upload your resume and TixelJobs AI will compare it against Data Engineer at Skyscanner. Get a match score, missing keywords, and improvement tips before you apply.
Free preview · Your resume stays private
About the Role
About Skyscanner
Everyone loves travelling, but planning is not without its challenges ✈️. That's why we've spent 20 years building tools that turn travel-planning chaos into a breeze. Today, around 100 million travellers count on us every month to skip the whole “47 browser tabs open” phase and find flights, cars, and hotels quickly and easily 💻.
Joining Skyscanner means becoming part of a global brand that's striving to become the planet's go-to travel hack accessible for all 🌍.
Our vision? To be the world's number one travel ally. (Ambitious? 💪 Yes, but, hey, that's what got us here)
About the role
(Hybrid)
Your mission: Join our distributed systems area to design, build and scale the pipelines and platforms that power decision-making across Skyscanner. From analytics to experimentation, your work will help 100 million travellers find their perfect trip — faster, smarter, smoother.
Your impact: You’ll shape the backbone of our Databricks ecosystem, championing modern data engineering practices and raising the bar on data quality, governance and performance. In short: if it moves data, you’ll help make it better.
What you'll be doing
- Designing scalable pipelines: Building and maintaining robust Spark/PySpark and SQL pipelines to process large-scale datasets reliably and efficiently.
- Orchestrating with confidence: Creating and managing data workflows that keep our data fresh, trusted and right where it needs to be.
- Powering our Lakehouse: Implementing and optimising data solutions on Databricks, leveraging Delta Lake and modern Lakehouse architecture.
- Structuring data the smart way: Applying Medallion Architecture principles (Bronze, Silver, Gold) to transform raw data into high-quality, analytics-ready assets.
- Championing governance: Using Unity Catalog to enable access control, lineage tracking and metadata management — because great data needs great guardrails.
- Elevating quality and performance: Establishing data quality monitoring (Monte Carlo or similar), optimising pipelines for performance and cost, documenting architecture, and contributing to code reviews and engineering best practices.
About you
- Experienced in data engineering: You bring 3+ years of experience building and maintaining production-grade data pipelines and infrastructure.
- Fluent in Python and SQL: You’re confident writing efficient, maintainable code for large-scale data processing.
- Spark-savvy: Hands-on experience with Apache Spark and PySpark is second nature to you.
- Airflow-ready: You’ve built and supported reliable production workflows using Apache Airflow.
- Lakehouse literate: You’ve worked with Databricks and Delta Lake, and understand Medallion Architecture patterns.
- Governance and modelling minded: You’re comfortable with data modelling concepts and understand governance principles such as Unity Catalog.
Ready to apply?
This job is active. Apply now to get in early.