Senior AI & Data Platform Engineer (NAM Portugal)

Job ID: 5682

 

We are seeking a technically driven and motivated Data Platform Engineer to join our AI and Data Innovation team. This role is central to building and evolving our internal data platform, with a focus on data engineering tooling, pipeline automation, and platform enablement. You will be hands-on from day one, contributing to the infrastructure that powers both our data capabilities across the organization.

 

At Nordea, we see that the world is changing fast – and we want to be one step ahead of the curve. That's why we're deeply committed to providing financial solutions for tomorrow to our customers. We're creating an agile environment where we experiment and grow together - and we need your ideas and personal background. With us, you'll be in good company with a chance to make your mark on something bigger.

 

Nordea Asset Management (NAM) is the centre of investment management in the Nordea Group and in the Asset & Wealth Management division. NAM is the largest asset manager in the Nordics with the vision of being a leading European Asset Manager. We want to do this by delivering returns with responsibility. We meet customer demands and guide our customers in the right direction in asset selection while ensuring prudent ESG practices. The group has more than 30,000 employees. NAM has around 900 employees and manages more than EUR 325 billion of assets for institutional, wholesale, and retail clients across the Nordic region and the globe.

 

About this opportunity

 

You will join our AI and Data Innovation team based in Lisbon, embedded in a cross-functional environment where engineering and innovation meet. Your primary focus will be on building and maintaining the data platform tooling that underpins our data and AI initiatives. You will contribute to driving platform adoption across the organization and act as a technical bridge between the data platform and our AI Lab. This is a hands-on role — expect to write code, build pipelines, and ship real solutions.

 

• The role is based in Oeiras (Quinta da Fonte).
• It’s expected you to work 100% on-site in the first 6 months (with flexibility) and after on an Hybrid regime (3 days in the Office + 2 days from home).

 

What you’ll be doing

 

Key responsibilities:

• Enabling teams by design, building and maintaining data platform tooling and infrastructure, leveraging technologies such as Snowflake, DBT, DLT and Airflow.
• Develop and maintain CI/CD pipelines to support reliable and automated data workflows.
• Contribute to shared infrastructure-as-code practices using Terraform and containerisation with Docker.
• Support the adoption and enablement of the data platform across business and technical teams, producing documentation and reusable components.
• Act as a technical bridge between the data platform and the AI Lab, ensuring data infrastructure is ready to support AI and LLM-driven use cases.
• Collaborate with engineers and data practitioners to identify improvements and new capabilities within the platform.

 

Who you are

 

Collaboration, Ownership, Passion and Courage are our core values at Nordea AM. We especially value collaboration within our team.

 

To succeed in this role, we believe that you:

• Are eager to learn and get things done — you enjoy building things and are not afraid to get your hands dirty.
• Have a foundational understanding of data engineering concepts and curiosity about how modern data platforms work.
• Can write Python code and are comfortable picking up new libraries and tools as needed.
• Have had some exposure to workflow orchestration concepts — familiarity with Airflow or similar tools is a plus, not a requirement.
• Have a basic awareness of CI/CD practices and what good software delivery looks like.
• Are curious about AI and LLM tooling (RAG, agentic workflows, etc.) — no hands-on experience needed, just genuine interest.

 

Your soft skills:

• Curious and self-driven with strong interest in data science and AI technologies.
• Ability to work collaboratively in a cross-functional team environment.
• Efficient and delivery oriented.
• Persistent and det