Senior Data & Analytics Engineer

hackajob is partnering directly with  and Jet2holidays to hire for this role.
At      and   Jet2

Holidays  , 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 working
Annual pay reviews
A generous discretionary profit-share scheme
The opportunity to work with a modern data stack and shape analytics at scale
What youll be doing
As 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 use
Implementing  complex data models and transformations  using SQL and  dbt , with a strong understanding of how upstream transformations feed downstream analytical use cases
Working with existing enterprise data models and dimensional structures, confidently navigating and extending them to support new analytics requirements
Owning and contributing to the enterprise data warehouse, including dimensional models and analytical data sets that serve both technical users and non-technical business stakeholders
Collaborating 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 early
Working closely with analytics, data science, and visualisation teams to ensure data products are fit for purpose, performant, and trusted
Supporting production data assets, including monitoring, issue resolution, and continuous improvement
Helping drive a data-first culture, contributing to data enablement activities, analytics best practices, and knowledge sharing across the data community
Acting as a senior technical contributor within the team, influencing standards, patterns, and ways of working
What youll bring
Were looking for someone who is analytics-engineering-led, with enough data engineering experience to work confidently across the full data lifecycle.
Essential experience
Strong experience building and maintaining analytics pipelines using SQL-first transformation patterns, ideally with dbt
Solid understanding of data warehousing concepts, including how dimensional and analytical models are used downstream, without requiring deep ownership of modelling design decisions
Advanced SQL skills, with the ability to write, read, and optimise complex queries across large datasets
Experience working with a cloud data warehouse such as Snowflake (preferred), Big Query, Redshift, or Synapse
Experience working in a modern cloud environment (AWS, GCP, or Azure), with exposure to core services such as cloud storage and orchestration
Experience working in an Agile delivery environment (Scrum and/or Kanban), with strong communication skills and the confidence to work directly with stakeholders at all levels
Desirable / supporting experience
Experience contributing to or supporting data ingestion pipelines, including APIs and event-driven data sources
Familiarity with orchestration tools (e.g. Airflow) and ELT architectures
Experience implementing or working with data CI/CD pipelines (for example, dbt tests, deployment pipelines, or automated checks). We currently use Azure Dev Ops
Working knowledge of Python for data-related tasks, automation, or light engineering work
An interest in data quality, observability, and analytics engineering best practices
Why this role is different
This 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 on
Apply modern analytics engineering practices at scale
Work with a contemporary stack: AWS, Snowflake, dbt, Airflow, SQL, and Python
Influence how data is modelled, trusted, and used across the organisation