At a Glance
- Tasks: Design and optimise data pipelines for our core lakehouse ecosystem.
- Company: Join On the Beach, a leader in travel innovation since 2003.
- Benefits: Enjoy 25 days holiday, discounts on holidays, and flexible working hours.
- Other info: Collaborative culture with opportunities for professional growth and wellbeing events.
- Why this job: Make a real impact by transforming raw data into trusted products.
- Qualifications: Strong Python and SQL skills; experience with cloud data platforms.
The predicted salary is between 50000 - 70000 £ per year.
We’re On the Beach! Since 2003, we’ve been rewriting the rules of how people discover, book and experience their perfect getaway. We’re looking for a Data Engineer to help design, build and optimise the data pipelines that power our core lakehouse ecosystem. This role sits at the heart of our data platform, helping turn raw, complex source data into reliable, structured and performant data products that can be trusted by teams across the business. You’ll work across batch and event-driven data, supporting the way we ingest, transform, test and make data available for analytics, reporting, AI use cases and future data products.
About the Role: We’re looking for a Data Engineer to help design, build and optimise the data pipelines that power our core lakehouse ecosystem.
What you’ll be doing day to day: As a Data Engineer, you’ll work closely with Data Engineering, Analytical Engineering, Product, Commercial and Technology teams to build high-quality data pipelines and platform capabilities. You’ll help improve how data moves through the business, making sure our pipelines are reliable, observable, cost‑effective and built using strong software engineering practices.
You’ll be responsible for:
- Designing, building and maintaining robust data pipelines across batch, streaming and event-driven data sources
- Ingesting, cleansing and transforming raw application, operational and enterprise data into reliable, structured data products
- Working with lakehouse technologies such as Databricks, Delta Lake, BigQuery or similar cloud data platforms
- Supporting data readiness for analytics, machine learning and AI‑enabled use cases, including structured and unstructured datasets
- Improving pipeline reliability, performance and cost efficiency through monitoring, observability and operational best practice
- Building automated tests, documentation and validation checks to improve data quality and reduce downstream issues
- Working closely with Analytical Engineers and stakeholders to make sure upstream data products are fit for reporting, insight and business use
- Applying engineering standards across version control, code review, CI/CD, deployment and incident resolution
- Using AI‑assisted engineering tools where appropriate to support development, testing, documentation and optimisation
- Contributing to data governance, security, naming standards and data contract practices across the platform
You’ll likely bring experience in:
- Strong Python and SQL skills for data manipulation, cleansing, transformation and pipeline development
- Building and maintaining production data pipelines in a cloud or lakehouse environment
- Working with Databricks, Delta Lake, Delta Live Tables, BigQuery, Snowflake or similar technologies
- Batch processing, workflow orchestration and data transformation patterns
- Event-driven or streaming data concepts, including ingestion patterns, APIs or event routing
- Applying software engineering practices to data, including Git, pull requests, testing, documentation and CI/CD
- Monitoring and troubleshooting data pipelines, including performance, reliability and cost considerations
- Working with data quality checks, data contracts, governance standards or access controls
- Collaborating with engineers, analysts and business stakeholders to turn data requirements into practical, maintainable solutions
- Making pragmatic decisions in fast‑moving environments, balancing delivery, quality and long‑term maintainability
Nice to have:
- Experience with Spark, Databricks Workflows, Delta Live Tables or medallion‑style data architecture
- Exposure to real‑time streaming technologies, event‑driven architecture or API‑based ingestion
- Experience preparing data for machine learning, vector indexing, AI agents or generative AI applications
- Experience using AI tools such as GitHub Copilot, Claude, Gemini or similar to support development, debugging, testing or documentation
- Understanding of data lineage, catalogue tooling, access management or enterprise governance frameworks
What success looks like: Success in this role is about building data pipelines and products that teams can trust. You’ll help improve the reliability, quality and performance of our data platform, making it easier for teams across On the Beach to access and use the data they need. You’ll reduce friction for downstream analytics and AI use cases by creating well‑structured, well‑tested and well‑documented data products. You’ll also contribute to a strong engineering culture within the data team, where standards are clear, pipelines are observable, and continuous improvement is part of how we work.
Benefits:
- 25 days holiday plus your birthday off
- Generous discount on holidays, plus you will receive 2 extra days annual leave on top of your holiday allowance to use whilst you’re away on your On the Beach package holiday
- Access to Learnerbly learning platform, plus workshops, courses and professional qualifications
- Enhanced maternity, paternity, shared parental leave and adoption pay, plus other family friendly support
- Employee Assistance Programme and free access to counselling
- Simplyhealth Optimise Health Plan
- Company Sick Pay scheme
- Regular wellbeing events
- Gym discount
- Share Incentive Plan (SIP)
- Death in Service cover
- Onsite subsidised coffee shop
- The Sandbox (our very own bar)
- Food and drink discounts across a number of venues in Manchester City Centre
- Regular social events
- Cycle to Work scheme
Ways of working: Our full time hours are 37.5 per week, but we don't have rigid working hours so you can find the working pattern that's right for you. We have core working hours between 10am - 4pm, so we can collaborate and enjoy the social side of work. We also have hybrid working so we all work from home and from our Aeroworks office in Manchester City Centre. As a team we are in the office 2 days per week (usually Tuesday & Wednesday).
Data Engineer employer: On the Beach
On the Beach is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Data Engineer role based in Manchester City Centre. With a strong focus on employee growth, we offer access to professional development resources, generous holiday allowances, and a range of wellbeing initiatives, all while promoting a flexible working environment that balances personal and professional life. Join us to be part of a dynamic team that values your contributions and supports your career journey in the exciting travel industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at On the Beach.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like On the Beach.
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We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at On the Beach, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at On the Beach. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at On the Beach
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at On the Beach!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
