We seek a Data Engineer to become a key contributor in building reliable data foundations for analytics, optimization, and AI-driven use cases. In this role, you will design and implement scalable data and machine learning pipelines, leveraging cloud technologies (Microsoft Azure), Python, and big data frameworks such as Apache Spark, to transform and deliver high-quality data solutions that support business processes and enable data-driven decision-making across the organization.

You might be our missing piece if you have:

• A completed degree in Computer Science, Business Informatics, Industrial Engineering, or a comparable engineering or natural sciences field

• At least 2 years of professional experience in designing and implementing data and/or machine learning pipelines, ideally within a large enterprise environment

• A solid understanding of business domains and processes, with the ability to translate business needs into data-driven solutions

• Experience working in interdisciplinary teams and collaborating effectively across functions

• Hands-on experience with Microsoft Azure and relevant cloud services

• Strong knowledge of Python or the Python data ecosystem (e.g., pandas, NumPy, scikit-learn, PySpark)

• Practical experience with Apache Spark for large-scale data processing

• Familiarity with containerization technologies such as Docker and Kubernetes enabling scalable and cloud-native application development

• Knowledge of Infrastructure as Code (IaC) concepts and tools (e.g., Terraform) for automated and reproducible infrastructure provisioning

We would be thrilled if you have:

• Experience with platforms and tools such as Databricks, Grafana, or Power BI

• Exposure to building and operating scalable, cloud-native data solutions

• A proactive mindset toward continuous improvement and optimization in data engineering practices

• A strong sense of ownership and accountability in delivering high-quality data solutions

• A collaborative attitude and enthusiasm for working in dynamic, cross-functional environments

• A sense of belonging while reading about our culture
  

We will be working together on:

• Building reliable data foundations that support analytics, optimization, and AI-driven use cases

• Designing, developing, and maintaining scalable data and ML pipelines.

• Optimizing existing data workflows to improve performance, reliability, and efficiency.

• Working with cloud-based data platforms (Microsoft Azure) to integrate and manage data solutions

• Collaborating with interdisciplinary teams to deliver data-driven solutions aligned with business needs

• Continuously improving data engineering practices, tooling, and processes to support innovation and scalability