Big Data Engineer

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 Big Data Engineer 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.

We offer you a fast-paced work environment in a diverse team with exposure to Dell teams across the globe. You will be part of a dynamic, collaborative and cross-functional team focused on making significant business impacts.

You will:

• 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.

Take the first step towards your dream career
Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements:

• Solid SQL Knowledge and skills in Python or other programming skills.

• 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.

Desirable requirements:

• 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.

Salary starting from: 3 250 Euro/gross monthly

Who we are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 1st May 2024

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.

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Dell’s Flexible & Hybrid Work Culture

At Dell Technologies, we believe our best work is done when flexibility is offered.

We know that freedom and flexibility are crucial to all our employees no matter where you are located and our flexible and hybrid work style allows team members to have the freedom to ideate, be innovative, and drive results their way. To learn more about our work culture, please visit our locations page.