Senior Data Engineer

Description:


COMPANY

We have disrupted the way people travel since we started 25 years ago, and we don't intend on stopping. We may be facing the biggest challenge in our history, but we are confident that throughout the pandemic we have taken the right action to build back stronger and better - and we want you to play a part in that and #belongherewithus.

We know that flexibility, balance and wellbeing are more important than ever right now. Whether that's working remotely, part time, or needing extra support when times are tough - we are always #happytotalkflex.

JOB PURPOSE

With significant investment into our data platforms and the chance to work with some fascinating data points, this is an opportunity for you to be a part of an exciting journey in supporting our vision of becoming the most data-driven airline in the world.

You will join as a Senior Data Engineer, providing technical leadership to the Data Engineering team. You will play a key role in ensuring that the team is adhering to data best practices while designing, building and maintaining production-grade data pipelines and data products across various business domains, and delivering them onto a cutting-edge distributed data platform.

JOB ACCOUNTABILITIES

• Work with onshore and offshore Data Engineers to deliver end-to-end production-grade Data Solutions (data pipelines/ingestion/curations/outbounds/API's),
• Drive the business to harness the power of data within easyJet, championing the central Data Platform and Data Product adoption for all analytical needs.
• Work with Technical Architects to define patterns and standards for data solution designs.
• Work with Business Analysts and Product Owners to understand requirements and use this to define the acceptance criteria for the technical scope and delivery of these requirements.
• Work with Data Scientists to optimise and productionise machine learning models
• Create the design and support documentation for all data pipelines/products that go into Production service.
• Catalogue our data assets to better enable our consumers to understand what is available, where they exist and how to gain access to them.
• Through research and hands-on exposure, deliver proofs of technology, playback to internal teams, and convince stakeholders to adopt where value can be realised.
• Deliver via cross-functional fast-paced agile 'data product' delivery teams, demonstrating a 'release within sprint' mentality.
• Support the development of individual Data Engineers through mentoring and coaching to improve development standards, domain knowledge and exhibiting the behaviours we expect.
• Drive improvements within the team demonstrating thought-leadership; finding ways to eliminate waste, embed new practices, improve quality, and guide the team through adopting modern development practices such as paired programming and test-driven development.
• Provide oversight of project deliverables and code quality going into the next shippable release, keeping a particular eye on release management aspects.

EXPERIENCE & BEHAVIOURS REQUIRED

Demonstrable experience working on leading large data projects and product delivery: supporting design work for the data products, along with playing a key role in feature engineering and operationalisation of these features into live service.

• Work with the business, data scientists and analytics teams to determine how best to solve the business problem through the use of Data Engineering approaches.
• Strong commercial experience in solving business problems with the use of data.
• Strong stakeholder management skills - often interfacing with the business to understand strategy and it is also important to be able to influence direction.
• Wealth of experience in productionising large scale data product solutions (batch or real-time solutions) - using distributed engines/frameworks such as Spark.
• Strong understanding and exposure of modern engineering practices / operating models (TDD, CICD, DevSecOps, DataOps, MLOps)
• Operationalising Data Science models at scale is desirable
• Databricks experience desirable
• AWS Cloud native services desirable - AppFlow, Glue, SageMaker
• Coach and support the Data Engineers

#LI-JB1 #LIHYBRID