Senior Data Engineer

Kin + Carta
London
10 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

The role

is central to maintaining a balance between the flexibility and scalability of data lakes and the structured query and performance benefits of data warehouses.

What you can expect

Create and maintain data pipelines to extract, transform, and load (ETL) data from various sources into a data warehouse or data lake. Ensure the data pipelines are efficient, scalable, and reliable. Integrate data from different sources, such as databases, APIs, logs, and external data providers. Ensure data quality and consistency during the integration process. Design and implement data models, including relational databases, NoSQL databases, and data warehouses, to support data analytics and reporting. Develop and manage data warehouses or data lakes to store structured and unstructured data. Perform data transformation and data cleansing to ensure data is in a usable format for analysis. Implement data enrichment and validation processes. Implement data security measures and access controls to protect sensitive data. Monitor data pipelines and data infrastructure for issues and performance bottlenecks. Debug and resolve data-related problems in a timely manner. Automate routine data engineering tasks to reduce manual intervention and improve efficiency. Maintain documentation for data pipelines, processes, and data models. Collaborate with data scientists, data analysts, software developers, and other cross-functional teams to meet data-related requirements. Contribute to the development of the organization's data strategy, aligning data engineering efforts with business goals.

The type of person we’d like to meet:

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field  5 years of experience working in Data Proficiency in ETL processes and tools Familiarity with databases and data warehousing Proficiency in Python, Java, or Scala Experience with cloud platforms Familiarity with data lakes and warehouses Understanding of data quality and governance Proficiency in managing data pipelines Knowledge of data visualization tools Effective teamwork and communication skills Willingness to stay updated on industry trends Written and verbal technical communication skills with an ability to present complex technical information in a clear and concise manner to a variety of audiences. Current hands-on implementation experience required.

Nice to have:

Knowledge in Data Science Understanding of Machine Learning  Experience in NoSQL Database  Familiarity with Real-Time Data Processing  Containerization Skills Familiarity with DevOps  Data Pipeline Monitoring Tools (e.g., Apache Airflow) Knowledge in Data Security  Expertise in Domain-Specific  Data Engineering Certifications Big Data Certifications

What we offer

This is a full-time position that comes with an attractive compensation; Premium health insurance that guarantees fast access to contracted health services in Kosovo, Albania, North Macedonia, Bosnia & Hercegovina, Serbia, Slovenia, and Croatia; Vacation Plan; Mental Health Support Program; Great opportunity for career development; Training policy for technical and other skills-related events, courses, and certifications; Performance Policy that paves the roadmap for personal career development; Hybrid working mode; Access to e-learning platforms like Udemy, Coursera, etc; Refreshments at our offices; The annual team building that gathers together the offices from Prishtina, Sofia, Veliko Tarnovo, and Skopje.

The interview process at Kin + Carta

Here’s what to expect from the interview process at Kin + Carta: 

Intro Call with the Talent Team (30mins) – If your skills and experience match the role requirements, our Talent team will contact you to arrange a call. The aim of this call is to get to know you and for you to find out more about Kin + Carta. This call can be held either by telephone or Zoom. After this call, if we feel like you are a good match for the role, you’ll be invited to a first-stage interview.

First-Stage Interview (60minutes) -This will typically be a Q&A style interview, lasting approximately 1h. This process is designed to help our team find out about your skills and experience but also what you enjoy and what motivates you. It’s a great opportunity for you to ask our team questions and learn more about us! 

Making a Decision- Following the interview process, our hiring team will get together to discuss feedback and make a final decision. We aim to get back to you as soon as we possibly can! 

Our average recruitment process takes aroundthree to four weeks. You will be assigned a dedicated member of our Talent team to support you throughout the process. 

We will always do our best to accommodate any reasonable adjustment requests. Please just let us know how we can make the interview process more accessible for you.

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.