Data Engineer

November 7, 2024

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iGenius

Augmented Analytics • Conversational Analytics • NLQ • Artificial Intelligence

Description

• Work somewhere with the creativity of a scaleup and expertise of an enterprise. • We are looking for a savvy Data Engineer to join our growing team of analytics experts in Milan. • You’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. • Should 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.

Requirements

• At least two 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.

Benefits

• 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.

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