Lead Data Engineer

Luton/Hybrid

Please read the following job description thoroughly to ensure you are the right fit for this role before applying.

JOB PURPOSE

The Lead Data Engineer is responsible for the technical design, delivery and implementation of data solutions within the IT estate. The role achieves this through a combination of exceptional technical ability and inspirational leadership.. The Lead Data Engineer works closely with the data engineering leadership team and wider stakeholders to deliver IT change that help easyJet be the leading data driven airline.

JOB ACCOUNTABILITIES

• Serve as the technical expert responsible for designing and delivering production-grade data solutions to support the breadth of use-cases across the business.
• Champion the distributed data platform and drive Data Product adoption, ensuring the data assets are catalogued to enable consumers to understand what is available, where they exist and how to gain easy access to data.
• Provide direct line management to a small team of Data Engineers. This includes managing their personal development, providing technical support and guidance, and ensuring their work meets the required standards.
• Work within cross functional teams of internal and external personnel to deliver data solutions at an enterprise level.
• Identify new and emerging technology, methods, trends and techniques in the Data Engineering space; assess and communicate
• Work directly with Data Science and Analytics to identify existing or future opportunities to deliver end-to-end data product solutions that drive business value.
• Responsible for ensuring Data Engineering solution designs meet the relevant functional and non-functional requirements and adhere to the wider IT technical standards.
• Responsible for verifying requirements, defining the Data Engineering components, developing an implementation and QA approach, manging technical debt, and providing thought leadership for all data solutions.
• Work with the Data Engineering Leadership team to identify and implement internal process improvements, such as automating manual processes, optimising data solution delivery and improving our ways of working.
• Apply appropriate risk mitigation actions by regularly reviewing those controls in place and processes/activities within your remit. (e.g. maintain Data Engineering risk register)

KEY SKILLS & BEHAVIOURS

• Leadership;lead your team by example and inspire those around you. Help your team understand the vision and how their work contributes to the wider easyJet organisation.
• Team management; understand and encourage working in an agile model, supporting and leading onshore and offshore data engineers. Identify and implement improvements (technical or otherwise) to make the data engineering teams more effective.
• Clear communication;can communicate effectively in both written and verbal forms with technical and non-technical audiences alike.
• Complex problem-solving ability; structured, organised, process-driven and outcome-oriented. Able to use historical experiences to help with future innovations.
• Passionate about technology;enjoy being hands-on and learning about new technologies, particularly in the data field.
• Self-directed and independent;able to take general guidance and the overarching data strategy and identify practical steps to take.

TECHNICAL SKILLS REQUIRED

• Solid understanding of data concepts and data modelling principles; applied across traditional warehousing, OLTP and modern data lakes.
• Significant experience designing and building data solutions on a cloud based, big data distributed system.
• Significant experience with Python, and experience with modern software development and release engineering practices (e.g. TDD, CI/CD).
• Significant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Arrow, MapR).
• Good understanding of software engineering principles.
• Strong SQL background – comfortable writing efficient SQL.
• Experience working with a range of cloud-based big data technologies (e.g. HDFS, Blob Storage, Spark, Kafka, Delta, Hive, Oozie, NiFi).
• Experience using enterprise scheduling tools (e.g. Apache Airflow, Spring DataFlow, Control-M)
• Experience with Linux and containerisation.
• Cloud computing experience (AWS, GCP, Azure)
• Experience with supporting big data cloud-based applications in Production (e.g. administration, configuration management, deployment, monitoring, debugging, and performance tuning).
• Understanding of Data Management principles (security and data privacy) and how they can be applied to Data Engineering processes/solutions (e.g. access management, data privacy, handling of sensitive data (e.g. GDPR))
• Understanding of Data Science Tooling for ML (e.g. MLFlow, Sagemaker), Data Analytics Tooling for dashboarding/visualisation (e.g. Tableau, Looker, Power BI) and interactive API’s/Web Apps (e.g. R-Studio, Shiny, Flask, Django).

DESIRABLE

• Airline experience
• Worked on regulatory/data privacy requirements in a data lake architecture, e.g. GDPR data handling
• Cloud-based OLAP experience – building and deploying cubes.
• Provisioning infra-as-code automatically – serverless data pipelines. (GitHub Actions, Jenkins, Terraform)
• Worked with modern lakehouse platforms – e.g. Databricks, Snowflake
• Solution architecture background – thinking beyond the data layer.
• Data Lake migrations away from Hadoop into the cloud.

BENEFITS

Competitive base salary

Up to 20% bonus

25 days holiday

BAYE, SAYE & Performance share schemes

7% pension

Life Insurance

Flexible benefits package

Excellent staff travel benefits