- 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.
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