Lead Data Engineer

Overview

In this role, you will lead the design, delivery and scaling of production-grade data solutions across easyJet’s IT estate. You’ll shape a distributed data platform and data products that power decision-making across the business. You’ll manage and develop a team of Data Engineers and Analytics Engineers, ensuring high-quality delivery. You’ll work with cross-functional teams to deliver enterprise-data initiatives and stay at the forefront of emerging technologies. This is a chance to impact how data drives strategy in a fast-paced, collaborative airline environment.

Pay / Benefits

• Up to 20% maximum bonus
• Private Medical Insurance
• 7% pension contributions
• Excellent staff travel benefits
• 25 days of annual leave + bank holidays
• Annual credit towards an easyJet holiday

Responsibilities

• Lead design, delivery and implementation of robust, scalable data solutions for diverse business use cases
• Champion evolution and adoption of distributed data platform and data products
• Manage and develop a team of Data Engineers and Analytics Engineers
• Collaborate with cross-functional teams to deliver enterprise-level data initiatives
• Partner with Data Science and Analytics teams to unlock opportunities and deliver end-to-end data products
• Ensure solutions meet functional and non-functional requirements and align with IT standards
• Drive automation, optimisation and improved ways of working
• Stay at the forefront of emerging technologies and inject innovation into the organisation
• Provide technical leadership, manage technical debt and shape QA approaches
• Act as deputy for the Data Engineering Technology Manager when required

Key requirements

• Proven leadership experience with ability to inspire and develop technical teams
• Strong experience designing and building cloud-based, distributed data platforms
• Advanced Python and SQL skills with CI/CD and TDD practices
• Experience with big data frameworks such as Apache Spark or similar
• Solid understanding of data modelling, data warehousing, OLTP and data lake architectures
• Experience working with cloud ecosystems such as AWS, Azure or GCP
• Familiarity with Kafka, Airflow, Hive, Delta, or similar technologies
• Strong understanding of software engineering principles and production support
• Experience with Linux, containerisation and enterprise scheduling tools
• Knowledge of data governance, security and data privacy principles including GDPR
• Confident communicator, able to present complex technical concepts to varied audiences
• Proactive, self-directed mindset with strong problem-solving skills

• confident communicator
• proactive mindset
• problem-solving
• Python
• SQL
• CI/CD

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