Data Engineer

About us:

We are a Y Combinator / Latitud backed micro-lending platform in Mexico led by people from companies such as Capital One, Bain & Company, Konfio, DiDi, Clip, Klarna, etc. We are hyper focused on making sure that customers improve their financial lives significantly through their relationship with us. In a very short time, we have achieved significant traction with exceptional consumer outcomes and unit economics. We are also starting to build and incorporate AI into our operations, so this is a great place to work for anybody who has ambitions to build real time applications of AI. Our goal is to build the biggest AI enabled fintech platform in Mexico and eventually LatAm.

Description of position:

We are looking for a Data Engineer to help us design, build and optimize our data infrastructure on AWS. In this role, you will be responsible for developing efficient pipelines, structuring scalable databases, implementing monitoring systems to run the application and developing the necessary infrastructure for machine learning models.

If you enjoy working with large volumes of data, automating processes and developing robust solutions, we want to meet you!

Responsibilities:

1. Design and develop scalable and efficient data pipelines in AWS (using tools such as AWS Glue, Lambda, S3, Redshift, etc.).
2. Create and optimize storage models (data lakes, data warehouses) in the cloud.
3. Implement monitoring systems for the application and data infrastructure.
4. Design and implement infrastructure to run machine learning models, ensuring scalability and resilience.
5. Implement data quality and governance processes to ensure its integrity and security.
6. Collaborate with data scientists and analysts to deliver clean data sets ready for modeling and analysis.
7. Monitor and improve the performance of data systems and models.

What we are looking for:

1. Experience in data infrastructure development, data engineering or similar roles (at least 1+ year of experience).
2. Solid knowledge of SQL and Python.
3. Experience with data processing tools such as Airflow, Spark or dbt.
4. Familiarity with cloud platforms (AWS).
5. Ability to work with relational and non-relational databases.
6. Experience in data integration from multiple sources and query optimization.
7. Proactive approach to problem solving and ability to work autonomously.

Bonus points if you have experience in:

1. Data modeling for financial or credit analysis.
2. Experience with AWS tools.