Arcube | Airline Loyalty Data Engineer

Arcube
Manchester
4 months ago
Applications closed

Who are we? ✈️

Arcubeis a UK-based startup and we built one of the industry’s first ‘Post-Flight Technologies’. Our AI-powered software analyzes passenger data after they disembark from a flight, enabling them to convert otherwise idle points into personalized ancillaries for future bookings. By leveraging ancillaries in a unique way, we drive repeat bookings, increase revenue, and build customer loyalty.


We are a small but highly capable team that values speed in building technology and execution. Our goal is to grow rapidly and establish ourselves as market leaders in the new and emerging category of the Post-Flight Experience.



The Role

We’re looking for an Airline Loyalty Data Engineer with expertise in airline loyalty systems and data workflows. You will design and build ETL pipelines to process loyalty transactions, integrate with passenger datasets, and enable personalization and marketing use cases. With a strong understanding of airline loyalty systems and cloud-based tools, you’ll develop scalable solutions and play a key role in shaping Arcube’s platform. As an early team member, you will receive meaningful ownership in Arcube for wearing multiple hats and being at the forefront of creating an industry-first product that will reshape the future of airline technology.


Key Responsibilities⚙️

  • Be instrumental in the development of Arcube’s post-flight platform, particularly with data extraction, transformation and understanding parts of our product.
  • Build ETL pipelines to manage loyalty and ancillary transactions (e.g., points accrual, redemptions, tier upgrades).
  • Manage & optimize Arcube’s AI data models by monitoring customer usage.
  • Enable data to be used in downstream use cases like customer segmentation, personalization, and targeted marketing.
  • Work with ML engineers to optimise and re-train models based on insights, usage and business aims.



Required Qualifications & Skills

  • Strong software engineering background, with a minimum Bachelor's degree in Computer Science or other related field.
  • 2+ years expertise with working with airline technology, specifically with the loyalty CRM, ancillary management and other components within PSS. Background in NDC, GDS or Offer & Order is a Plus.
  • How airlines manage and process data internally, specifically for loyalty and ancillary management applications.
  • You have a good foundation in computer science: data transformation (cleansing, enrichment, aggregation), integration (scheduling, orchestration) and modelling (schema design, warehousing).
  • Hands-on experience with languages and applications such as Python, NodeJS, SQL, Apache Airflow, Apache Spark, Amazon Redshift and Docker.
  • Design, implement, and maintain ETL pipelines and databases such as MongoDB and DynamoDB.



Salary & Benefits 

  • Competitive Base Pay 
  • Six Figure Equity Package (with vesting)
  • The role is remote, but if you're based near Manchester, United Kingdom, you have the option to work from our city-centre office.

We’re happy to disclose our compensation and equity during the interview process.



Hiring Process

First Stage - Introductory Call

  • A 30-minute conversation with our founders to discuss your experience in the travel industry and introduce you to Arcube.

Second Stage - Home Task & Presentation

  • We’ll provide a short system/data challenge (designed to take less than 2 hours) at least 4 days before your second interview.
  • During the interview, you’ll present your solution, share your thought process and the approaches you considered.

Final Stage – Deep Dive and Conclusion

  • A deeper conversation to understand your motivations for joining Arcube, preferences and your alignment with a startup working style. 

Offer - If we’re aligned, we’ll be excited to extend an offer and welcome you to the team!

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Jobs

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Jobs

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.