Sr. Data Engineer

Promtior; Buenos Aires; Híbrido; ARS 135.892.000 - 226.487.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

20 paid days off per year

Hybrid work model

Flex Days: monthly team activities

Professional development courses

Internal clubs (soccer, padel, running

Descripción de la vacante

Promtior is seeking a hands-on Senior Data Engineer to design and implement scalable data pipelines and data models powering AI-driven solutions. You will work across architecture, ingestion, validation and collaboration with product teams to deliver reliable data products.

Requirements include 4+ years of experience, Databricks production experience, advanced Python/SQL, cloud familiarity, and strong data quality discipline. Hybrid work and English communication are expected.

Formación

• 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.

Responsabilidades

• Design and evolve the data platform architecture for scalable growth.
• Build end-to-end pipelines ingesting from APIs, databases, files and providers.
• Create reliable data validation, observability and monitoring.
• Collaborate with product and business stakeholders to translate problems into data solutions.
• Define engineering standards for testing, documentation and deployment.

Conocimientos

Databricks

Python

SQL

ETL/ELT pipelines

Data modeling

REST APIs

Cloud (AWS/Azure/GCP)

Git & CI/CD

English communication

Production debugging

Educación

Bachelor's in Computer Science or related field

Herramientas

Databricks

Descripción del empleo

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 2023, 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