Data Engineer II - Customer Growth Marketing

Data Engineer II - Customer Growth Marketing

Do you want to solve some of the hardest problems for business leveraging ML/AI? Do you want to learn how to build algorithms that scale - most of our use cases start with 10 million+ rows of data.

Our data scientists & engineers are helping to shape our marketing strategy for a digital world.

Join us to do the best work of your career and make a profound social impact as a Data Engineer II - Customer Growth Marketing on our Data Engineering team in Bratislava, Slovakia.

What you'll achieve

The models and solutions you deliver will be the essential ingredient we use to supply our customers & sales with relevant product recommendations and creative breakthroughs to our business.

• Feature engineering: Stitching together and aggregation of multiple large data sets working with the data scientist to a desired format. You will need to optimize both queries and architecture to support big data sets. SQL is usually the preferred language, but some Spark jobs are necessary.
• Data pipelining: Once the initial dataset are prepared, it is normally run through a further pipeline to prepare it for modelling. Here you will create features that make ML/AI algorithms work (e.g. translating text into category variables). Python/R is usually the preferred language.
• Work with other engineers and data scientists to solve some of the hardest business problems.
• Learn what it takes to build, deploy & scale ML/AI models in real-world.
• Build analytical data sets on which model's will be built. This would entail two key tasks - feature engineering on large datasets and optimization of our pipelines to drive scalability.

• Solid SQL Knowledge.
• Education (Bachelor's degree or higher) in Computer Science, Mathematics, or a related technical field, or equivalent practical experience
• Attention to detail, Attention to detail, Critical thinking and open to learn.
• Willing to mentor junior team members.
• You have professional experience. 5+ years of experience in Data or BI engineering dealing with large complex data scenarios

• Skills in Python or other programming skills.
• Proven ability to work with varied data infrastructures - including relational databases, Data Warehouses, column stores, NoSQL databases, and file-based storage solutions. Exposure to Software engineering and machine learning or machine learning pipelines is a plus.