hackajob is partnering directly with Jet2.com and Jet2holidays to hire for this role.At Jet2.com and Jet2Holidays , were here to deliver amazing journeys literally. Everything we do is guided by a Customer First mindset, creating unforgettable holidays and flights. None of that happens without great data, and we couldnt do it without our amazing people.As a Senior Analytics Engineer, youll work as part of a multi-disciplinary, agile data delivery team, contributing to the build and evolution of analytics-ready data across our platform. This role is analytics engineering first , with a strong emphasis on implementing and maintaining complex models in our Silver and Gold data layers , rather than defining modelling strategy from scratch.Youll join a multi-disciplinary, agile data delivery team working alongside other analytics and data engineers, data scientists, test engineers, and data visualisation specialists.Whats in it for you?Remote workingAnnual pay reviewsA generous discretionary profit-share schemeThe opportunity to work with a modern data stack and shape analytics at scaleWhat youll be doingAs a Senior Analytics Engineer, youll focus primarily on the analytics layer of the platform, while working closely with data engineering colleagues on upstream ingestion and orchestration.Key responsibilities include:Building and maintaining analytics-ready data models in our cloud data warehouse, transforming raw and curated data into trusted, well-documented datasets for business and analytical useImplementing complex data models and transformations using SQL and dbt , with a strong understanding of how upstream transformations feed downstream analytical use casesWorking with existing enterprise data models and dimensional structures, confidently navigating and extending them to support new analytics requirementsOwning and contributing to the enterprise data warehouse, including dimensional models and analytical data sets that serve both technical users and non-technical business stakeholdersCollaborating with data engineers on the ingestion and orchestration of data from a wide range of sources (databases, flat files, APIs, and event-driven feeds), ensuring downstream analytics requirements are considered earlyWorking closely with analytics, data science, and visualisation teams to ensure data products are fit for purpose, performant, and trustedSupporting production data assets, including monitoring, issue resolution, and continuous improvementHelping drive a data-first culture, contributing to data enablement activities, analytics best practices, and knowledge sharing across the data communityActing as a senior technical contributor within the team, influencing standards, patterns, and ways of workingWhat youll bringWere looking for someone who is analytics-engineering-led, with enough data engineering experience to work confidently across the full data lifecycle.Essential experienceStrong experience building and maintaining analytics pipelines using SQL-first transformation patterns, ideally with dbtSolid understanding of data warehousing concepts, including how dimensional and analytical models are used downstream, without requiring deep ownership of modelling design decisionsAdvanced SQL skills, with the ability to write, read, and optimise complex queries across large datasetsExperience working with a cloud data warehouse such as Snowflake (preferred), BigQuery, Redshift, or SynapseExperience working in a modern cloud environment (AWS, GCP, or Azure), with exposure to core services such as cloud storage and orchestrationExperience working in an Agile delivery environment (Scrum and/or Kanban), with strong communication skills and the confidence to work directly with stakeholders at all levelsDesirable / supporting experienceExperience contributing to or supporting data ingestion pipelines, including APIs and event-driven data sourcesFamiliarity with orchestration tools (e.g. Airflow) and ELT architecturesExperience implementing or working with data CI/CD pipelines (for example, dbt tests, deployment pipelines, or automated checks). We currently use Azure DevOpsWorking knowledge of Python for data-related tasks, automation, or light engineering workAn interest in data quality, observability, and analytics engineering best practicesWhy this role is differentThis is not a pure platform data engineering role, nor is it a purely reporting-focused analytics role. Its an opportunity to:Own and shape the analytics layer that the business relies onApply modern analytics engineering practices at scaleWork with a contemporary stack: AWS, Snowflake, dbt, Airflow, SQL, and PythonInfluence how data is modelled, trusted, and used across the organisationTPBN1_UKTJ