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For Companies At a Glance
- Tasks: Design and maintain data pipelines for AI-driven solutions in a leading airline.
- Company: Join a top airline client with a focus on innovation and collaboration.
- Benefits: Attractive daily rate, hybrid work model, and potential contract extension.
- Why this job: Make an impact by enabling advanced analytics and supporting AI integration.
- Qualifications: Expertise in Python, SQL, and cloud platforms; experience in data engineering roles.
- Other info: Opportunity for international travel and dynamic team collaboration.
The predicted salary is between 36000 - 60000 £ per year.
We have an exciting contract job opportunity for a Data Engineer / KPI Dashboard for one of our leading airline clients.
Role Purpose
The Data Engineer will design, build, and maintain robust data pipelines and architectures to enable AI-driven solutions for business, ensuring frameworks can scale across all OpCos. This role demands consultancy-level technical depth combined with strong delivery discipline.
Contract – 6 months with possibility to extend
Location – Waterside (UB7 0GB)
Work Model: Hybrid – 3 days per week onsite
Pay - attractive daily rate (Inside IR35)
Key Responsibilities
- Develop and optimize data pipelines for ingestion, transformation, and storage.
- Ensure data quality, integrity, and security across systems.
- Collaborate with Data Scientists and Analysts to enable advanced analytics.
- Implement best practices for scalability and performance in cloud environments.
- Support integration of MRO AI Solutions into business operational workflows.
- Design data architecture and pipelines that support multi-OpCo deployment, ensuring modularity and interoperability.
Required Skills & Experience
- Expertise in Python, SQL, and modern ETL frameworks.
- Hands-on experience with cloud platforms (AWS preferred).
- Strong knowledge of data modeling and API integration.
- Proven experience in developing, testing, and deploying data solutions into production environments, ensuring reliability, scalability, and maintainability beyond proof-of-concept or prototype stages.
- Familiarity with airline or logistics data domains is a plus.
- Significant experience in similar roles, with a proven ability to integrate quickly into new teams and deliver immediate value.
- Initial co-location with client teams in London is essential to ensure close collaboration. Candidates must also be prepared to travel internationally during later stages to facilitate group-wide deployment.
Preferred Consulting-Level Competencies
- Ability to design enterprise-grade data solutions under tight timelines.
- Strong stakeholder engagement and solution-oriented mindset.
- Experience in advisory or consulting roles for data engineering projects.
- Track record of creating high-impact outcomes and driving stakeholder satisfaction from day one.
- Ability to implement standards and frameworks for scalable data solutions across multiple operating companies.
Data Engineer-KPI Dashboard employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer-KPI Dashboard
✨Tip Number 1
Network like a pro! Reach out to your connections in the airline industry or data engineering field. Attend meetups, webinars, or even casual coffee chats. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, architectures, and any projects you've worked on. This is your chance to demonstrate your expertise in Python, SQL, and cloud platforms like AWS. Make it easy for potential employers to see what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your consultancy-level skills. Be ready to discuss how you've tackled tight timelines and engaged stakeholders in past projects. Practice articulating your thought process when designing scalable data solutions – this will set you apart from the competition.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly can sometimes give you an edge over other candidates. So, get your application in and let’s land that job together!
We think you need these skills to ace Data Engineer-KPI Dashboard
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and cloud platforms like AWS. We want to see how your skills align with the job description, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. Mention your experience in developing data pipelines and your ability to work collaboratively with Data Scientists and Analysts.
Showcase Relevant Projects: If you've worked on projects that involved data architecture or ETL frameworks, make sure to include them. We love seeing real-world examples of your work, especially if they relate to the airline or logistics sectors!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Hays
✨Know Your Data Inside Out
Before the interview, dive deep into the data engineering concepts relevant to the role. Brush up on your Python, SQL, and ETL frameworks. Be ready to discuss how you've optimised data pipelines in the past and how you ensure data quality and security.
✨Showcase Your Cloud Skills
Since the role involves cloud platforms, particularly AWS, make sure you can talk about your hands-on experience with these technologies. Prepare examples of how you've designed scalable data architectures and integrated solutions in cloud environments.
✨Collaborate Like a Pro
This position requires working closely with Data Scientists and Analysts. Think of examples where you've successfully collaborated with cross-functional teams. Highlight your communication skills and how you’ve contributed to advanced analytics projects.
✨Be Ready for Real-World Scenarios
Expect scenario-based questions that test your problem-solving abilities. Prepare to discuss how you would handle tight timelines and stakeholder engagement. Show them your solution-oriented mindset and how you can deliver value from day one.
