Data Engineer

About us

AEOS is a tech and data company at the forefront of innovation in TV advertising. We help drive TV understanding and engagement using Data Engineering and Machine Learning. Our clients include some of the most sophisticated and data-driven advertisers, such as L’Oréal, DAZN, eBay, and Audi. We are headquartered in Croatia and Germany, serving clients across the EU.

Our Data Science and Engineering teams design and build scalable data solutions, ML pipelines, and applications that process large volumes of TV and audience data.

We are looking for an experienced Data Engineer to join our team in Zagreb. Our ideal candidate has strong software engineering fundamentals and broad technical interests, and is comfortable working across different parts of the data stack - from building data pipelines to orchestration, deployment, CI/CD, and infrastructure improvements.

What you will be doing

• Designing, implementing, and maintaining data processing pipelines in Spark, for large volumes of structured and unstructured data
• Writing clean, modular, reusable, and maintainable code in Scala and/or Python
• Improving the architecture, performance, scalability, and reliability of existing data pipelines
• Working with Apache Airflow to orchestrate production workflows and contributing to migrations and improvements of our orchestration infrastructure
• Building and improving CI/CD pipelines and development/deployment processes
• Deploying, monitoring, and troubleshooting data pipelines in production
• Supporting data and ML workloads and helping bring new solutions reliably into production
• Collaborating with Data Scientists, Data Engineers, DB Engineers, and Product teams on end-to-end technical solutions
• Contributing to technical decisions and continuously improving our engineering practices and data platform
• Taking ownership of technical initiatives from design and implementation through deployment and production operation

What we expect from you

• Master’s degree in Computer Science, Engineering, Statistics, or related field
• 4+ years of professional software or data engineering experience
• Strong software engineering fundamentals, including object-oriented programming, algorithms, data structures, and clean code principles
• Strong programming skills in Python and/or Java/Scala (experience with Scala is a plus)
• Experience with Apache Spark and distributed data processing
• Experience designing, building and optimizing production-grade ETL/data pipelines for performance and reliability
• Good understanding of SQL and relational databases
• Experience working with Git and Linux
• Familiarity with containers and Docker, experience with Kubernetes is a plus
• Experience with, or a good understanding of, workflow orchestration tools such as Apache Airflow
• Understanding of CI/CD principles, automated software delivery and scripting
• Experience with cloud environments; AWS is a plus
• Ability to independently investigate problems and work across different parts of a technical system
• Strong analytical and problem-solving skills
• Proficient English

We don't expect you to know every technology in our stack. We value strong engineering fundamentals, broad technical curiosity, and the ability to learn new technologies and take ownership of problems across system boundaries.

What we offer you

• Work in an international, ambitious team disrupting the TV advertising industry
• Opportunity to work on challenging data and ML systems using real-world datasets
• Broad technical exposure across data engineering, software engineering, cloud infrastructure, and ML systems
• Opportunity to influence technical architecture and engineering practices
• Collaboration with experienced engineers and data scientists
• Exposure to leading technologies and some of the biggest names in the internet and advertising industry
• Competitive salary and benefits
• Flexible working hours and home office options
• Subsidized kindergarten support for employees with children
• Multisport

If you recognize yourself, reach out to us by sending your CV to [email protected].

By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.