expertise in building distributed data processing systems, machine learning model lifecycle and automation coupled
good knowledge of Azure ecosystem
proven record developing Python - SQL and Spark are a plus
good experience in data structure and algorithm; good knowledge in Terraform and Databricks is a plus
deep knowledge of machine learning algorithms and techniques and strong software engineering fundamentals
developing a production quality code, writing understandable documentation are mandatory

Ihre Aufgaben

The customer unit is a multinational team of advanced analytics and artificial intelligence experts as well as data venture managers and UX specialists. Their mission is to create the right conditions for the most promising new technologies and new data-driven business models to develop and, eventually, hatch. The team is responsible for identifying most promising venture ideas, prioritizing them according their impact potential, giving them the space and resources to thrive.

Tasks:

your responsibility is to develop and productionize end-to-end high-performing Date engineering solutions that goes beyond building Data pipelines (Extract, Transform and Load data ), working with unstructured and structured data in Batch and stream mode
ou will get the opportunity to building machine learning pipelines aligned to business needs
as a pragmatic Data Engineer you will push the boundaries by introducing new technologies and development principles
you will partner and collaborate in a cross-functional team of data scientists and system engineers
as a team member you use Data Architecture principles to better build the next generation energy solutions – in this case focusing on solar energy potential and computer vision modelling
the given project is set to establish a blueprint architecture for scalable ML & computer vision product at the customer, built on Azure