Data Engineer

About Inetum, Positive digital flow:

Inetum is an IT services company that provides digital services and solutions and a global group that helps companies and institutions to get the most out of digital flow. The Inetum group is committed towards all these players to innovate, continue to adapt and stay ahead. With its multi-expert profile, Inetum offers its clients a unique combination of proximity, a sectorial organization and solutions of industrial quality. Operating in more than 26 countries, the Group has nearly 27,000 employees and in 2020 generated revenues of €1,965 billion.

Inetum Romania is an important player in the IT services and solutions market in our country, with over 15 years of activity. It is a stable, growing and profitable company with over 500 employees who provides IT consulting services, infrastructure and software development assistance, digital services implementation and support.

In an Agile format, our teams work on cloud initiatives, application development, business intelligence, automation and digitalization projects that contribute to the profit and evolution of our clients. The diversity of our projects offers team members the opportunity for learning and growth. The company had a turnover of 20 million EURO in 2021.

As a big data engineer in the Finance Data Project you are trusted with the implementation of data processing flows according to the standards set by your peers and the business side. We keep in touch with multiple teams which raise various data requirements for their web applications or business intelligence tools.

A part of our daily work has been already organized in a rigorous way, but the other can be cast by your hand according to dynamic needs. Your previous experience and the way in which you apply it in our environment is of utmost importance.

Concepts in order of importance:
git, Hadoop, Spark, SQL
Scala or Python, CI/CD pipelines
Cloud technologies (role management, scalable clusters)
Data exploration and visualization tools (notebooks, BI tools)

During project definition
•Design of data ingestion chains
•Design of data preparation chains
•Basic ML algorithm design
•Data product design
•Design of NOSQL data models
•Design of data visualizations
•Participation in the selection of services / solutions to be used according to the uses
•Participation in the development of a data toolbox

During the iterative realization phase
•Implementation of data ingestion chains
•Implementation of data preparation chains
•Implementation of basic ML algorithms
•Implementation of data visualizations
•Using ML framework
•Implementation of data products
•Exposure of data products
•Setting up NOSQL databases
•Implementation in distributed mode of treatments
•Use of functional languages
•Debugging distributed processes and algorithms
•Identification and cataloging of reusable elements
•Contribution to the evolution of labor standards
•Contribution and opinion on data processing problems

During integration and deployment
•Participation in problem solving

Career plan (professional, academic, and financial)
Medical insurance
Official training's and certifications
Lunch tickets
Yearly professional evaluation
Professional and friendly working environment.