Data Engineer

Inetum; Porto; Presencial; EUR 42 000 - 66 000; Tempo integral

Resumo da oferta

Inetum is seeking a Mid-Level Data Engineer to design, optimize, and maintain scalable data pipelines, ensuring reliability and performance of data solutions. You will collaborate with Data Science teams to integrate and operationalize ML models in production environments.

The role emphasizes building robust data processing, optimizing workflows for large datasets, and contributing to best practices in software development within a multinational digital services leader.

Qualificações

• 3+ years of experience in Data Engineering.
• Advanced proficiency in Python and SQL.
• Demonstrated ability to design robust, maintainable, and highly scalable solutions for large-scale data processing.
• Hands-on experience with in-memory data processing libraries such as Polars (or equivalent).
• Strong knowledge of software development best practices and version control.
• Experience deploying, monitoring, and maintaining ML pipelines in production environments.

Responsabilidades

• Design, develop, and maintain scalable data pipelines.
• Optimize data processing workflows for large-scale datasets.
• Build and manage data ingestion solutions from multiple sources.
• Ensure data quality, reliability, and performance across platforms.
• Collaborate with Data Science and Engineering teams to deploy and operationalize ML solutions.
• Contribute to software engineering best practices and continuous improvement.

Conhecimentos

Python

SQL

Data pipelines

PySpark

Polars

Distributed processing

Git

CI/CD

ML production

Ferramentas

Databricks

Apache Airflow

AWS

Azure

GCP

Descrição da oferta de emprego

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good.

Job Description

We are looking for a Mid-Level Data Engineer to design, optimize, and maintain complex data pipelines, ensuring the scalability, reliability, and performance of data solutions. In this role, you will also collaborate with Data Science teams to integrate and operationalize machine learning models in production environments.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines.
• Optimize data processing workflows for large-scale datasets.
• Build and manage data ingestion solutions from multiple sources.
• Ensure data quality, reliability, and performance across platforms.
• Collaborate with Data Science and Engineering teams to deploy and operationalize ML solutions.
• Contribute to software engineering best practices and continuous improvement initiatives.

Qualifications

• Proven experience of 3+ years in Data Engineering.
• Advanced proficiency in Python and SQL.
• Demonstrated ability to design robust, maintainable, and highly scalable solutions for large-scale data processing and performance optimization.
• Hands-on experience with in-memory data processing libraries such as Polars (or equivalent).
• Solid experience with distributed data processing frameworks, particularly PySpark.
• Strong knowledge of software development best practices.
• Experience with Git, CI/CD pipelines, and software testing methodologies.
• Experience deploying, monitoring, and maintaining Machine Learning pipelines in production environments.

Nice to have:

• Experience with modern data platforms such as Databricks.
• Experience orchestrating workflows using tools such as Apache Airflow.
• Knowledge of cloud platforms (AWS, Azure, or GCP).