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 ( 30 mins ) – 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 ( 60 minutes) – 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 around three 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.
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