We seek a talented and communicative Data Engineer with knowledge and skills that cover the entire data lifecycle — from ingestion to delivery (serve) — as well as competencies in orchestration and infrastructure.
This role involves building, maintaining, and optimizing scalable data solutions.

Python: Strong understanding of Python and its application in data processing, including libraries such as pandas
Airflow: Experience creating DAGs, maintaining workflows, and integrating with dbt-core
DBT (dbt-core): Development and maintenance of models and macros
Experience converting/migrating SQL code into dbt
SQL Server: Advanced knowledge, including: Performance tuning, Query optimization, Performance evaluation
Git: Experience with layered deployment structures aligned with infrastructure teams
Medallion Architecture: Operational understanding of the Medallion architecture (implementation not required)
DataOps & On-Premise Environments: Practical, hands-on experience
English: Minimum level B2 (Upper-Intermediate)
Nice to Have: Kubernetes: Intermediate knowledge (deployments, Helm, on-premise environments, and data-related use cases)
Nifi: Basic operational knowledge
Spanish: B1 level
Data Science: Experience with document extraction (NLP using Python).

Data Engineer

Key skills