Sr.
Data Engineer
About Promtior
Promtior is at the forefront of the Agentic AI revolution, delivering cutting‐edge solutions that transform businesses across industries — bridging technology and people to turn AI into a real competitive advantage.
Since ****, we've helped organizations boost operational efficiency through tailored Agentic AI solutions, from discovery and development to full implementation, across three core lines: AI Product Delivery (predictive analytics, intelligent automation, AI‐driven chatbots, image processing), AI Department as a Service (LATAM‐based teams that integrate directly with our clients' teams), and AI Adoption Consulting (helping companies find and act on AI opportunities across their business).
We're a team held together by genuine relationships, constant exchange, and shared learning.
We believe innovation happens when people feel included and collaborate with purpose, and we aim for professional growth to go hand in hand with personal well‐being.
About the Role
This is not a narrow ETL development role.
We are looking for a hands‐on senior engineer who moves comfortably between architecture, implementation, troubleshooting and conversations with product and business stakeholders.
What you'll own
Architecture
Help design evolve the architecture for a data platform, lakehouse and warehouse environment, as the product grows.
Design clean, maintainable data models that support product features, analytics, reporting and AI/ML use cases.
Make pragmatic architectural decisions.
Pipelines
Design and build end‐to‐end pipelines ingesting from APIs,



operational databases, third‐party platforms, files and external data providers.
Build scalable ingestion, transformation and orchestration workflows, from raw ingestion through curated, product‐ready datasets.
Design incremental pipelines that handle changing source data.
Optimize pipelines and queries for performance, reliability and cost.
Reliability
Implement data quality, validation, observability and monitoring.
Identify inconsistencies and anomalies across multiple data sources.
Define engineering standards for testing, documentation, version control and deployment.
Collaboration
Translate operational problems from product and business stakeholders into technical solutions.
Requirements
Minimum 4+ years of data engineering experience
Production experience with Databricks.
Advanced Python and advanced SQL.
Experience designing ETL/ELT pipelines.
Strong understanding of relational and analytical data modeling.
Experience integrating REST APIs, databases, files and third‐party systems.
Experience designing incremental pipelines and handling changing source data.
Strong understanding of data quality, lineage, observability and reliability.




Hands‐on experience with at least one major cloud provider (AWS, Azure or GCP).
Comfortable with Git, CI/CD, automated testing, modular and reusable code, production debugging, and infrastructure and deployment concepts.
Professional English (see Language below).
Nice to have
Depth in Databricks, Spark and lakehouse architecture.
Having built a data platform from an early stage, rather than only maintaining an established one.
Domain experience in financial services, logistics, supply chain or trade data.
Ingestion from highly fragmented or poorly structured sources.
Document‐processing pipelines.
Data feeding AI/ML applications.
Data governance, lineage and security.
Working directly with U.S. clients or product teams.
Startup or product‐company experience.
How you work
You ask the right questions and understand the business problem behind the ticket.
You investigate unfamiliar datasets independently.
You challenge weak architectural decisions.
You design a solution and then personally build it.
You communicate trade‐offs clearly and operate comfortably with ambiguity.
You take responsibility for systems in production.
You raise the technical level of the people around you.
Benefits
20 paid days off per year.
Hybrid work model.
Flex Days: monthly team activities.
Professional development courses.
Internal clubs (soccer, padel, running, cinema).
Location
Montevideo, Uruguay.Buenos Aires, Córdoba, Corrientes or Chaco, Argentina.
Hybrid work arrangement
#J-*****-Ljbffr

📌 Sr. Data Engineer (Corrientes)
🏢 Promtior
📍 Corrientes