DEUS.ai

Data Engineer [Medior/Senior]

DEUS.ai Matosinhos, Portugal

IT Services and IT Consulting · 51-200 employees

Yesterday
data-engineer Mid (2-5 yrs) Full-time Spain
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About the role

Design, build, and optimize scalable data products and pipelines using cloud-native architectures and modern data platform principles. Collaborate with cross-functional teams to develop robust data foundations that support AI and machine learning solutions.

What they look for

Python SQL Apache Spark PySpark AWS Azure CI/CD GitHub Actions Data pipelines Data modeling Lakehouse DataOps Cloud-native architecture ETL ELT Automation

Requirements

Requires solid experience in designing end-to-end data pipelines and strong proficiency in Python, SQL, and Apache Spark. Candidates should have expertise in cloud data services and a deep understanding of modern data platform principles like Lakehouse and DataOps.

Benefits

Health insurance Flexible benefits Annual learning budget Mentorship Extra vacation days Hybrid work setup Social events

Full description

🏛 The DEUS Initiative

We're a team of curious minds who believe technology should serve people. Our mission is to unlock the potential of AI for humanity through solutions that are not just innovative, but also ethical and impactful. We're driven by a desire to simply make things better.

Our name is inspired by deus ex machina, not because we think we’re gods, but because we design AI that steps in to support, solve, and serve.

DEUS also stands for what we do best:

Data | Engineering | User Experience | Strategy

With offices in Amsterdam, Porto, and A Coruña, we collaborate on international projects that challenge us to think deeply, build with care, and design for human good.

Will you be part of what comes next?

⚜️ About You

This role is a great fit if you have:

  • Solid experience designing and implementing end-to-end data pipelines leveraging cloud services, with a strong focus on scalable, cloud-native architectures.
  • Strong programming skills in Python and SQL, plus automation and scripting capabilities.
  • Hands-on expertise with Apache Spark, PySpark, and modular data ingestion and transformation components.
  • Proficiency with cloud data services and platforms, such as AWS, Azure, or equivalent technologies.
  • Experience with CI/CD pipelines (GitHub Actions, cloud-native CI/CD tools, or similar) and Git-based version control.
  • A solid understanding of Lakehouse and modern data platform principles, supporting both structured and semi-structured data.
  • Knowledge of ELT/ETL design, data modeling, orchestration, and event-driven architectures.
  • Willingness to collaborate on AI Engineering projects, exploring how modern data platforms and engineering practices can enable innovative AI solutions.

Bonus points if you have:

  • Familiarity with data cataloging and governance tools, such as cloud-native data catalogs, Alation, Collibra, or similar.
  • Certifications in cloud data engineering, or Databricks.
  • Experience with serverless architectures and advanced cloud automation across AWS, Azure, or equivalent cloud environments.
  • Previous mentoring experience, contributing to DataOps best practices and the creation of reusable, scalable components.

⚜️ What You’ll Be Doing

  • Design, build, and optimize scalable data products and pipelines across cloud-based data platforms, following cloud-native architecture principles.
  • Develop reusable and modular components for data ingestion, transformation, and orchestration using appropriate cloud-native technologies.
  • Apply Lakehouse and modern data platform principles, ensuring data quality, governance, lineage, security, and scalability.
  • Develop and optimize Spark and PySpark workloads to improve performance, scalability, and cost efficiency.
  • Design, implement, and maintain CI/CD pipelines and automation workflows for data workloads, ensuring reliable and repeatable deployments across environments.
  • Work with cloud services and infrastructure to build secure, scalable, and maintainable data solutions across AWS, Azure, or equivalent platforms.
  • Collaborate closely with data product owners, architects, and business stakeholders to translate requirements into robust technical solutions.
  • Contribute to DataOps best practices, automation, monitoring, testing, and continuous improvement of data products and platforms.
  • Mentor junior data engineers and contribute to a culture of engineering excellence, knowledge sharing, innovation, and continuous learning.
  • Collaborate with AI Engineering teams and projects, contributing your data engineering expertise to build scalable data foundations that power AI and machine learning solutions.

(…and there’s always space to explore what excites you.)

⚜️ What You’ll Experience

  • Community: Join a friendly multicultural team that loves to connect, through regular social events, activities, and our yearly company retreat, Pantheon.
  • Flexibility: We encourage a hybrid setup, but there are no mandatory office days. You decide when to come in and how to manage your time.
  • Growth: We support your development with a €1000 annual learning budget, dedicated mentorship, and a clear growth framework. We do annual reviews to recognize your growth and make sure your salary reflects it.
  • Well-being: Benefit from health insurance, flexible benefits, extra vacation days with tenure, and regular check-ins to support your well-being.
  • Purpose: Drive real impact and take ownership of meaningful projects with global clients.

⚜️ A Place Where You Belong

At DEUS, we are deeply committed to building an environment where you can truly be your authentic self. We celebrate diversity in every dimension, fostering an atmosphere where every individual feels valued and respected.

We do not tolerate any form of discrimination. We maintain a clear 'no assholes' policy, applying to both our team and our clients, ensuring a respectful and positive dynamic for all.

We’re committed to an inclusive and accessible recruitment process. So please let us know how we can best support you on the application form.

Apply now if this sounds like a fit. We’d love to meet you.

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