Senior Data Engineer

Kin + Carta
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineering Lead: Lakehouse & DataOps

Senior Data Engineer (AI & MLOps, AWS, Python)

Senior Data Scientist & Engineer (Hybrid) for Sustainable Impact

Senior Data Infrastructure & MLOps Engineer

Senior Data Scientist & ML Engineer – Hybrid

Senior AI/Generative Data Engineer: LLMs, MLOps, Cloud

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.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.