Senior AI Engineer

2 semanas atrás

Lisboa, Lisboa, Portugal act digital Tempo inteiro


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. BigQuery, 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 (GenAI)
    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.

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