Data Engineer

On-siteJust posted

You will create and maintain automated data pipelines from various sources and business domains, including data modeling, transformation and preparation to support Business Intelligence and AI solutions.
You will play a key role in the company's digital transformation journey, helping to centralize and democratize enterprise data across business functions.
You will use Databricks as the primary platform to design, develop and operate scalable Lakehouse solutions.
You will explore, integrate and connect data from legacy enterprise applications such as SAP and other business systems, ensuring reliable data availability for analytics and AI use cases.
A significant part of your work will focus on enabling and supporting AI initiatives, requiring a strong interest in Artificial Intelligence, modern data architectures and emerging technologies.
You will be responsible for maintaining data reliability, integrity and availability while complying with Cybersecurity and IT security standards.
You will monitor and optimize ETL pipelines to ensure they remain reliable, efficient and performant.
Stay up to date with the latest developments and trends in Data Engineering and Artificial Intelligence, incorporating new methodologies into daily work.

Master's degree in Computer Science, Data Engineering, Applied Mathematics or similar field.
2+ years of experience as Data Engineer, Analytics Engineer or AI/Data Engineer.
Strong SQL and Python skills.
Experience with Databricks, AWS and modern Lakehouse architectures.
Experience building and maintaining scalable ETL/ELT pipelines.
Knowledge of data modeling, data warehousing and Delta Lake concepts.
Experience with Git and CI/CD practices.
Understanding of data governance, access control and data quality principles.
Strong communication skills and fluent English.

Nice to Have:

Experience with SAP data sources.
Experience integrating SharePoint and enterprise document repositories.
Knowledge of Power BI or similar BI tools.
Understanding of AI data architectures, including RAG, vector search and LLM applications.
Experience with Unity Catalog and Databricks governance capabilities.