Senior Ai Engineer / Data Engineer

Senior Ai Engineer / Data Engineer
Lisboa
Lisboa, Lisboa, Portugal

? Senior AI Engineer / Data Engineer (GCP / Airflow)

Location: Lisbon, Braga, or Coimbra (hybrid)

Language: English (minimum B2 level required)

Candidates must be currently living in Portugal.

About the Role:

We are looking for an experienced Senior AI Engineer / Data Engineer with at least 5 years of professional experience in data engineering or similar roles, and strong expertise in Google Cloud Platform (GCP) and Airflow (Cloud Composer).

The ideal candidate is highly proficient in Python, skilled in building and maintaining data pipelines and workflows, and comfortable working with SQL in complex environments.

Exposure to Generative AI foundations and Large Language Models (LLMs) will be considered a strong plus, though it’s not mandatory.

Key Responsibilities:

• Design, develop, and maintain data pipelines and workflows using Python and Airflow (Cloud Composer).
• Work with GCP services to implement scalable and reliable data solutions.
• Write and optimize SQL queries for data extraction, transformation, and loading (ETL).
• Collaborate closely with cross-functional teams (Data Science, ML Engineering, and Analytics) to ensure data integrity and efficiency.
• Participate in code reviews, share best practices, and contribute to continuous improvement of our data ecosystem.

Required Skills:

• Proficiency in Python for data processing and automation.
• Experience with Google Cloud Platform (GCP) (e. G. Big
  Query, Cloud Storage, Cloud Functions).
• Hands-on experience with Apache Airflow or Cloud Composer.
• Strong command of SQL and relational database design principles.
• Good communication skills in English (written and spoken, minimum B2 level).

Nice to Have

• Exposure to Generative AI (Gen
  AI) concepts and Large Language Models (LLMs) – at least 6 months of foundational knowledge (hands-on experience not required).
• Understanding of data orchestration, MLOps, or machine learning workflows in production.
• Familiarity with version control (Git) and CI/CD pipelines for data engineering projects.