DATA ENGINEER

Work somewhere with the creativity of a scaleup and expertise of an enterprise.
e are looking for a savvy Data Engineer to join our growing team of analytics experts in Milan.
ou’d be responsible for expanding and optimizing our data and data pipeline architecture, as well as for improving data flow and collection for cross-functional teams.
You’d support our AI Research Engineer, Machine Learning Engineers and Backend Developers on data initiatives, ensuring consistent data delivery architecture throughout ongoing projects.
hould you be successful, you would.
Create and maintain optimal data pipeline architectures Assemble large, complex data sets that meet functional and business requirements Identify, design, and implement improvements to internal practices.
automating manual processes, optimizing data delivery Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of sources What You Have At least four years’ proven experience in a data engineer role A degree in Computer Science, Applied Math, Informatics, Information Systems or similar Experience building processes supporting data transformation, data structure, metadata, dependency and workload management Advanced working knowledge and experience with relational databases, query authoring as well as working familiarity with a variety of databases, such as SQL and NoSQL Experience building and optimizing data pipelines, architectures and data sets Experience with Python or Scala.
Experience with distributed computing.
Hands-on experience with object-oriented design, coding, and testing patterns.
Knowledge of pipeline and workflow management tools (Airflow, Argo Workflows, …) Experience with CI/CD tools (Jenkins, Travis, Argo CD, Terraform...) Good understanding of Cloud and data models (data warehouse, data lake) and current engineering practices such as distributed architecture.
Experience with MLOps is a plus.
Experience with HPC is a plus.
Who You Are An enthusiastic individual, excited by the prospect of optimizing or even contributing to designing our company’s data architecture An analytical thinker with a passion for data Proactive, comfortable working alone or as part of a team Super organized Accurate, with strong attention to detail Familiar with Agile development Fluent in English Working at iGeniusWith a growing team in four offices — Milan, NYC, London and Lausanne — iGenius is a scaleup that thinks like an enterprise, where talented innovators can thrive and people come first.
That’s not all.
erks Learning Fridays.
If our team members know more, so do we.
That’s why we give everyone a training budget that they can spend on books, online courses or other training materials Smart Working.
Trains can be a drag, so we let our team members work from home when they can Salary is based on experience and topped up with other bonuses.
About iGeniusiGenius is an Italian AI company that develops language models and AI solutions tailored for highly regulated industries, including financial services and government.
With a mission to democratize business knowledge, iGenius is one of the top AI unicorns in Europe today.
iGenius’ flagship product, Crystal, is a Decision Intelligence tool that analyzes data in natural language, making it accessible for anyone within a business organization.
From Allianz to Intesa San Paolo, Crystal has become the AI solution of choice for a number of Fortune 500 companies.
This led Gartner to recognize iGenius as a “Cool Vendor” in the  AI Core Technologies category, as well as mention the company in its Market Guide for Conversational AI and include it in the Magic Quadrant for Analytics and BI platforms.
In June , iGenius released Italia, an open-source Foundational Large Language Model, developed in collaboration with Cineca, and trained entirely on high-quality native Italian sources.
That same month, iGenius launched a new enterprise solution called Unicorn, to support companies in adopting AI safely and effectively, with AI solutions tailored to their needs.
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