At a Glance
- Tasks: Lead a team to design and build scalable data solutions for a seamless airport experience.
- Company: Join Cavu, a forward-thinking company transforming airport travel with innovative technology.
- Benefits: Enjoy 25 days holiday, flexible benefits, gym access, and a supportive work environment.
- Other info: Be part of a diverse team committed to innovation and continuous improvement.
- Why this job: Make a real impact on travel experiences while growing your career in data engineering.
- Qualifications: Experience in leading data projects, strong Python and SQL skills, and cloud expertise.
hackajob is collaborating with MAG (Airports Group) to connect them with exceptional professionals for this role.
About CAVU
For airports, for partners, for people. We are Cavu. At Cavu, our purpose is to find new and better ways to make airport travel seamless and enjoyable for everybody — from the smallest ideas to the biggest transformations. Every day is an opportunity to create better travel experiences. From our revenue-accelerating single-platform technology, Propel, through to our world-class hospitality venues including 1903 and Escape Lounges, our solutions make travel smoother for passengers and more profitable for our clients and partners. We know that to bring your best ideas, you need the space to think, the support to grow, and the freedom to be your authentic self. Whether you're working from our offices, from home, in our lounges, or on the road, we provide an environment where you can create, innovate, and help transform airport travel. Together, we can reach new heights. Together, we are Cavu.
The role
We're looking for an experienced Lead Data Engineer to play a key role in shaping and evolving Cavu's data platform, enabling data-driven decision making across our products and business. Leading a small team of Data Engineers, you'll combine hands-on technical expertise with technical leadership, mentoring colleagues while designing and delivering scalable data solutions that support analytics, machine learning and real-time reporting. Working closely with Data Scientists, Analysts and stakeholders across Technology and the wider business, you'll develop modern cloud-based data platforms, build robust ETL pipelines and champion best practice in data engineering, governance and architecture. This is an exciting opportunity to join a growing team building a globally unique platform using modern technologies, where you'll have genuine influence over technical direction and help solve complex commercial and customer challenges.
Key Responsibilities
- Lead, mentor and develop a team of Data Engineers, fostering a collaborative and high-performing culture.
- Design, build and maintain scalable data pipelines and ETL processes to support business-critical data solutions.
- Partner with Data Scientists, Analysts and business stakeholders to translate business requirements into robust technical solutions.
- Drive data quality by implementing validation, monitoring and governance best practice.
- Optimise the performance of databases, data warehouses and data lakes to support growing business demands.
- Evaluate and implement modern data technologies, tools and frameworks to enhance data processing and analytics capabilities.
- Define and promote data governance, privacy and security standards across the data platform.
- Work closely with Infrastructure and Operations teams to deploy, maintain and support cloud-based data solutions.
- Provide technical expertise when troubleshooting complex data issues and continuously improve engineering standards across the team.
What we need from you
- Previous experience as a Lead or Senior Data Engineer, with experience leading engineering projects or mentoring technical teams.
- Strong experience designing, building and maintaining ETL pipelines, data warehouses and scalable data platforms.
- Expert Python and SQL skills, with experience working with large datasets and distributed systems.
- Hands-on experience with AWS services, including Redshift, Lambda, EC2, Kinesis and Batch.
- Experience working with relational and NoSQL databases, alongside strong data modelling skills.
- A solid understanding of data governance, data quality and data security principles.
- Excellent stakeholder management, communication and problem-solving skills, with the ability to translate commercial requirements into technical solutions.
- A naturally curious, collaborative mindset with a passion for continuous improvement and modern data engineering practices.
What is in it for you
- 25 days holiday, increasing with service (up to 28)
- Option to buy up to 10 extra days
- 4 flexible bank holidays
- 10% company pension
- Annual bonus scheme
- On-site gym
- MediCash scheme
- A range of flexible benefits and discounts, including up to 50% off Cavu products such as Escape Lounges and Airport Parking
- Rail and retail discounts
- 2 paid volunteering days per year
- Access to health & wellbeing events, ID&E activities and learning opportunities
- Formal and informal development options, including mentoring programmes and learning grants
- Enhanced parental leave (T&Cs apply)
Equal Opportunities and Reasonable Adjustments
We're building something brilliant at Cavu: a diverse team of people who reflect the global customer base we serve. We're proudly part of MAG, and together we're on a mission to be number one in our industries — and that takes talent in all its forms. Whether this is your first role or your next big step, we want to hear from you, even if you don't think you tick every box. What matters most is what you bring. We're proud to be a Disability Confident employer. If you need any adjustments to support your application or interview, just let us know — we're committed to helping you perform at your best.
Our Colleague Communities play a big part in that journey, including Women's Network, Embrace (Race & Ethnicity), Fly with Pride (LGBTQIA), Mind Matters (Mental Health), PACT (Parents & Carers), RespectABILITY (Disability & Neurodiversity), and the Cavu Global ID&E Affinity Group.
Lead Data Engineer in Manchester employer: Mag
MAG is an exceptional employer, offering a dynamic work environment where innovation meets operational excellence. With a strong focus on employee growth and development, we provide comprehensive training and support to help you thrive in your role as a Technical Operations Engineer. Our commitment to a collaborative culture ensures that every team member's contributions are valued, making it a rewarding place to work in the fast-paced airport setting.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Mag!
✨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 Lead Data Engineer at Mag.
✨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 Mag.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer at Mag, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
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 Mag, 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 Mag. 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 Mag
✨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 Mag!
✨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.
