Grow is a Latam-based holding for micromobility and payments.

It is the result of the merger between Grin, the mexican scooter pioneer, and Yellow, a multimodal and payment player from Brazil.

About your job:

We are looking for a data engineer who can help us build a scalable data platform that serves every single person at Grow. You will be part of an early team that will establish data architecture, processes, and practices that serve as standards for the company. Your work will allow the business to make better decisions, data scientists to build better models, and engineers to scale applications. All based on a huge and ever increasing amount of data.

Here you are going to be responsible for:

  • Help define the vision and projects for the data engineering team
  • Build and own the core data pipelines that serve our hyper-growing requirements
  • Implement tracking of data quality and consistency
  • Develop and operate tools that support self-servicing data needs across the company
  • Work closely with product managers, software engineers, data scientists and data analysts to design and improve our data architecture

Double click in your routine:

  • Create and maintain a self serve data platform that allows anyone at the company to answer questions without your direct interaction
  • Work side-by-side with the infrastructure team to deploy and maintain the data infrastructure and tools
  • Keep your source organized in our git repository
  • Collaborate in building and enforcing the roadmap
  • Manage and prioritize your tasks efficiently

Our requirements for this position are:

  • 5+ years working as a data engineer or similar role
  • Experience designing data pipelines
  • Strong skills in at least one language (Python, Ruby, Scala, Java)
  • Advanced SQL and able to conduct performance tuning
  • Familiarity with MPP databases and data processing engines (Redshift, Snowflake, Spark, Presto)
  • Experience with data orchestration tools (Airflow)
  • Knowledge of data modeling and ETL best practices
  • Comfortable working in a cloud environment like AWS (DynamoDB, S3, Kinesis, Athena)


  • Startup environment
  • Flexible working hours
  • Work in a recently launched startup