Senior Data Engineer at IOL Inversiones

Language

Setup: Hybrid
Location: Buenos Aires, Autonomous City of Buenos Aires
Type: Full-time
Level: senior
Posted: May 11, 2026

Description

IOL InvertirOnline is hiring a Senior Data Engineer for its Data Management team to build and maintain reliable batch and streaming data pipelines, lakehouse architectures, data quality and governance controls, observability, and performance-optimized data systems. The role also includes defining department KPIs, enabling analysts and business stakeholders, and mentoring less senior engineers. Candidates need a technical degree, at least four years of data engineering experience, production Databricks experience, advanced Python, PySpark, SQL, cloud, and AI/ML experience, plus project leadership or formal mentoring. The position offers a flexible hybrid arrangement at the company's Palermo office in Buenos Aires, Argentina, with Swiss medical coverage and other benefits.

Required Skills

Databricks
Delta Lake
Spark Structured Streaming
Python
PySpark
SQL
Unity Catalog
Machine learning
dbt
Kafka

Additional Information

Minimum Education: Graduation in Systems Engineering, Computer Science, Mathematics, Statistics, or a related technical field; a technical degree with a proven track record is considered equivalent.
Required Previous Experiences: At least 4 years of data engineering experience responsible for production data pipelines and architectures.
At least 2 years of hands-on production Databricks experience, including concrete projects with Delta Lake and Spark.
Experience implementing machine learning or artificial intelligence solutions in production.
Independent leadership of at least one complex data project or formal mentoring of less experienced people.
Preferred Qualifications: Databricks Certified Data Engineer Associate or Professional, or ML Associate certification.
Experience integrating language models into data workflows or internal products using LangChain, LlamaIndex, or similar orchestrators.
Experience using dbt for data model transformations, testing, and documentation.
Experience with Kafka, Confluent, or Spark Structured Streaming for real-time data architectures.