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Inetum

Data Engineer

Inetum Ermesinde, Portugal

IT Services and IT Consulting · 10,001+ employees

5 d ago
data-engineer Mid (2-5 yrs) Full-time Portugal
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About the role

Design, develop, optimize, and maintain scalable data pipelines and ingestion solutions, ensuring data quality, reliability, and performance across platforms. Collaborate with Data Science and Engineering teams to deploy and operationalize machine learning solutions, while contributing to software engineering best practices and continuous improvement.

What they look for

Python SQL Data Engineering Data Pipeline Design Large-Scale Data Processing Polars PySpark REST APIs Data Ingestion Data Quality Machine Learning Deployment Git CI/CD Software Testing Databricks Apache Airflow

Requirements

Requires at least three years of data engineering experience, advanced Python and SQL skills, and experience with Polars or an equivalent library, PySpark, and REST API-based ingestion pipelines. Candidates should also have software development, Git, CI/CD, testing, and production machine learning pipeline experience; Databricks, Airflow, and cloud platform experience are advantageous.

Full description

Descrição da empresa

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.

Descrição do emprego

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.

Habilitações

  • 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.
  • Experience developing data ingestion pipelines leveraging REST APIs.
  • 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).

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