{"id":2621983,"url":"https://alion.io/job/easyjet-senior-data-platform-engineer","title":"Senior Data Platform Engineer","company":{"id":1758344,"name":"easyJet","domain":"easyjet.com","url":"https://alion.io/company/easyjet-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":84000,"max_usd":165000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":39},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Flink","optional":false},{"name":"GDPR","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Great Expectations","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Power BI","optional":true},{"name":"Tableau","optional":true}],"status":"live","first_seen_at":"2026-10-15T13:44:43Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T04:28:30Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Senior Data Platform Engineer\nLuton/Hybrid\nCompany\nWe are easyJet - a FTSE-250 listed, £multi-billion low-cost airline that serves tens of millions of customers every single year. If you’re reading this, you have probably already been an easyJet customer, and you’ll know that there is no more iconic (or Orange!) travel brand in Europe.\nWe fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low-cost travel easy - and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service.\nWhat makes us easyJet? Our Promise Behaviours - we are Safe, Bold, Welcoming and Challenging. Four Behaviours. One Spirit. One easyJet.\nJob Purpose\nWith a big investment into Databricks, and with a large amount of interesting data, this is the chance for you to come and be part of an exciting transformation in the way we store, analyse and use data in a fast paced organisation. You will join as a Senior Platform Data Engineer providing technical leadership to the Data Engineering team. You will work closely with our Data Scientists and business stakeholders to ensure value is delivered through our solutions.\nJob Accountabilities\nDevelop robust, scalable data pipelines to serve the easyJet analyst and data science community.\nHighly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala.\nWork with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploy machine learning models and algorithms aimed at addressing specific business challenges and opportunities.\nCoach and mentor the team (including contractors) to improve development standards.\nWork with Business Analysts to deliver against requirements and realise business benefits.\nBuild a documentation library and data catalogue for developed code/products.\nOversight of project deliverables and code quality going into each release.\nSenior Data Platform Engineer\nLuton/Hybrid\nCompany\nWe are easyJet - a FTSE-250 listed, £multi-billion low-cost airline that serves tens of millions of customers every single year. If you’re reading this, you have probably already been an easyJet customer, and you’ll know that there is no more iconic (or Orange!) travel brand in Europe.\nWe fly more than 1,207 routes, connecting 38 countries across Europe, and employ more than 18,000 colleagues. We’re on a mission to make low-cost travel easy - and whatever your role here, you’ll connect millions of people to what they love using Europe’s best airline network, great value fares, and friendly service.\nWhat makes us easyJet? Our Promise Behaviours - we are Safe, Bold, Welcoming and Challenging. Four Behaviours. One Spirit. One easyJet.\nJob Purpose\nWith a big investment into Databricks, and with a large amount of interesting data, this is the chance for you to come and be part of an exciting transformation in the way we store, analyse and use data in a fast paced organisation. You will join as a Senior Platform Data Engineer providing technical leadership to the Data Engineering team. You will work closely with our Data Scientists and business stakeholders to ensure value is delivered through our solutions.\nJob Accountabilities\nDevelop robust, scalable data pipelines to serve the easyJet analyst and data science community.\nHighly competent hands-on experience with relevant Data Engineering technologies, such as Databricks, Spark, Spark API, Python, SQL Server, Scala.\nWork with data scientists, machine learning engineers and DevOps engineers to develop, develop and deploy machine learning models and algorithms aimed at addressing specific business challenges and opportunities.\nCoach and mentor the team (including contractors) to improve development standards.\nWork with Business Analysts to deliver against requirements and realise business benefits.\nBuild a documentation library and data catalogue for developed code/products.\nOversight of project deliverables and code quality going into each release.\nKey Skills Required\nTechnical Ability: has a high level of current, technical competence in relevant technologies, and be able to independently learn new technologies and techniques as our stack changes.\nClear communication; can communicate effectively in both written and verbal forms with technical and nontechnical audiences alike.\nComplex problem-solving ability; structured, organised, process-driven and outcome-oriented. Able to use historical experiences to help with future innovations.\nPassionate about data; enjoy being hands-on and learning about new technologies, particularly in the data field.\nSelf-directed and independent; able to take general guidance and the overarching data strategy and identify practical steps to take.\nTechnical Skills Required\nSignificant experience designing and building data solutions on a cloud based, big data distributed system.\nHands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD), and software deployment automation with GitHub actions or Azure DevOps.\nExperience in testing automation of data transformation pipelines, using frameworks like Pytest or dbt Unit Test.\nComfortable writing efficient SQL and debugging.\nData warehouse operations and tunning experience in schema evolution, indexing, partitioning.\nHands-on IaC development experience with Terraform or CloudFormation.\nUnderstanding of ML development workflow and knowledge of when and how to use dedicated hardware.\nSignificant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam)\nFamiliarity with Databricks as a data and AI platform or the Lakehouse Architecture.\nExperience with data quality and/or and data lineage frameworks like Great Expectations, dbt data quality, OpenLineage or Marquez, and data drift detection and alerting.\nUnderstanding 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)\nDesirable Skills\nExperience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam.\nUnderstanding of the challenges faced in the design and development of a streaming data pipeline and the different options for processing unbounded data (pubsub, message queues, event streaming etc)\nUnderstanding of the most commonly used Data Science and Machine Learning models, libraries and frameworks.\nKnowledge of the development lifecycle of analytical solutions using visualisation tools (e.g. Tableau, PowerBI, ThoughtSpot)\nHands-on development experience in an airline, e-commerce or retail industry.\nWorked within the AWS cloud ecosystem.\nExperience of building a data transformation framework with dbt.\nWhat you’ll get in return\nCompetitive base salary\nUp to 20% bonus\n25 days holiday\nBAYE, SAYE & Performance share schemes\n7% pension\nLife Insurance\nWork Away Scheme\nFlexible benefits package\nExcellent staff travel benefits\nLocation & Hours of Work\nWe operate a hybrid working policy of 40% of the month spent with colleagues.\nWe look forward to your application and the possibility of you flying high with our team!\nApplication Process:\nInterested candidates should apply through our careers portal.\nReasonable Adjustments:\nAt easyJet, we are dedicated to fostering an inclusive workplace that reflects the diverse customers we serve across Europe. We welcome candidates from all backgrounds. If you require specific adjustments or support during the application or recruitment process, such as extra time for assessments or accessible interview locations, please contact us at . We are committed to providing reasonable adjustments throughout the recruitment process to ensure accessibility and accommodation\nMP2#\n\nKey Skills Required\nTechnical Ability: has a high level of current, technical competence in relevant technologies, and be able to independently learn new technologies and techniques as our stack changes.\nClear communication; can communicate effectively in both written and verbal forms with technical and nontechnical audiences alike.\nComplex problem-solving ability; structured, organised, process-driven and outcome-oriented. Able to use historical experiences to help with future innovations.\nPassionate about data; enjoy being hands-on and learning about new technologies, particularly in the data field.\nSelf-directed and independent; able to take general guidance and the overarching data strategy and identify practical steps to take.\nTechnical Skills Required\nSignificant experience designing and building data solutions on a cloud based, big data distributed system.\nHands-on software development experience with Python and experience with modern software development and release engineering practices (e.g. TDD, CI/CD), and software deployment automation with GitHub actions or Azure DevOps.\nExperience in testing automation of data transformation pipelines, using frameworks like Pytest or dbt Unit Test.\nComfortable writing efficient SQL and debugging.\nData warehouse operations and tunning experience in schema evolution, indexing, partitioning.\nHands-on IaC development experience with Terraform or CloudFormation.\nUnderstanding of ML development workflow and knowledge of when and how to use dedicated hardware.\nSignificant experience with Apache Spark or any other distributed data programming frameworks (e.g. Flink, Hadoop, Beam)\nFamiliarity with Databricks as a data and AI platform or the Lakehouse Architecture.\nExperience with data quality and/or and data lineage frameworks like Great Expectations, dbt data quality, OpenLineage or Marquez, and data drift detection and alerting.\nUnderstanding 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)\nDesirable Skills\nExperience in event-driven architecture, ingesting data in real time in a commercial production environment with Spark Streaming, Kafka, DLT or Beam.\nUnderstanding of the challenges faced in the design and development of a streaming data pipeline and the different options for processing unbounded data (pubsub, message queues, event streaming etc)\nUnderstanding of the most commonly used Data Science and Machine Learning models, libraries and frameworks.\nKnowledge of the development lifecycle of analytical solutions using visualisation tools (e.g. Tableau, PowerBI, ThoughtSpot)\nHands-on development experience in an airline, e-commerce or retail industry.\nWorked within the AWS cloud ecosystem.\nExperience of building a data transformation framework with dbt.\nWhat you’ll get in return\nCompetitive base salary\nUp to 20% bonus\n25 days holiday\nBAYE, SAYE & Performance share schemes\n7% pension\nLife Insurance\nWork Away Scheme\nFlexible benefits package\nExcellent staff travel benefits\nLocation & Hours of Work\nWe operate a hybrid working policy of 40% of the month spent with colleagues.\nWe look forward to your application and the possibility of you flying high with our team!\nApplication Process:\nInterested candidates should apply through our careers portal.\nReasonable Adjustments:\nAt easyJet, we are dedicated to fostering an inclusive workplace that reflects the diverse customers we serve across Europe. We welcome candidates from all backgrounds. If you require specific adjustments or support during the application or recruitment process, such as extra time for assessments or accessible interview locations, please contact us at . 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