Localization
: Lisbon or Porto
We are looking for a
Data Engineer Tech Lead
to join our IT Payments Data Team.
The team is responsible for the evolution and support of the payments product, designing, developing, and implementing
scalable and efficient data solutions
for the payments domain.
Main Responsibilities
Act as a
technical referent
for the team, developing code for processing and analyzing large and complex datasets (e.G., unstructured tracking data, large full-text datasets, graph data).
Design and implement
highly scalable batch and real-time data processing workflows
and components that provide data-driven functionality (e.G., search, recommendation, classification services), leveraging
machine learning, Big Data technologies, and distributed systems
.
Build, monitor, and operate data services within the infrastructure,
enhancing data quality, utility, and automating processes
.
Deploy solutions on
cloud technologies
, primarily
Google Cloud Platform (GCP)
.
Collaborate closely with
Data Scientists and Analysts
to support the design, implementation, and evaluation of algorithms, ML models, and other data-driven features.
Guide and mentor team members through technical challenges related to
data engineering and the tech stack
.
Required Skills & Qualifications
Education & Experience
Degree in
Computer Science, Information Technology, Computer Engineering, or a related field
.
3–9 years of experience in designing and implementing
scalable software and data-driven services
.
Technical Skills
Strong experience with
Big Data technologies
, data storages (relational databases, key-value stores),
data warehouses, data lakes, and lakehouses
.
Programming experience with
Spark, Python, Java, Scala
(for batch and real-time processing).
Experience building and optimizing
data pipelines for large datasets
.
Experience in
cloud environments
, especially GCP services (BigQuery, BigTable, Dataproc, GCS, Composer, GKE).
Familiarity with
low-code/no-code ETL tools
(e.G., YAML).
Strong
SQL skills
and experience with
Business Intelligence
.
Experience with
workflow management platforms
(Airflow) and collaborative tools (Jupyter).
Knowledge of
Agile methodologies
(SAFe/Scrum).
Understanding of
software development, CI/CD, DevOps, and QA practices
(e.G., XLRelease/XLDeploy, Terraform, Jenkins, Git, Bitbucket).
Nice to Have
Experience with
Microsoft Azure and Power BI
.
Familiarity with
AI/ML concepts and technologies
.
Experience in
information retrieval or extraction
is a plus.
Personal Skills
Strong
problem-solving and analytical skills
.
Excellent
communication and collaboration
skills.
Ability to
mentor and guide junior team members
.
Comfortable working in a
fast-paced, international, and cross-functional team environment
.