• Design, develop, and maintain robust, scalable data pipelines in Python to support real-time data ingestion and transformation.
  
• Work with messy or incomplete data sources to structure, clean, and integrate them into reliable datasets.
  
• Collaborate with product and ML teams to define data requirements and translate business needs into technical solutions.
  
• Rapidly prototype and iterate on data workflows to validate new ideas and capabilities.
  
• Architect scalable systems to support machine learning, anomaly detection, and automated evidence collection.
  
• Optimize pipelines for performance, quality, and cost efficiency in cloud environments.
  
• Ensure data integrity and reproducibility through documentation, testing, and monitoring.
• Contribute to the overall data strategy and infrastructure roadmap as the company scales.

AI is part of the core workflow, every day, for real work. This is not a traditional full-stack role where AI is a nice-to-have.

This role is for developers who:

• Think in terms of “prompt → generate → validate → refine → ship”
• Are comfortable letting AI write the first version of most things.
• Take responsibility for the correctness, security, performance, and maintainability of AI-assisted output.
• See AI as a force multiplier, not a threat to craftsmanship

You'll be onboarded to the tech team organization. You will be part of a team and will communicate with them via Slack and Google Meet. Periodic 1-on-1 meetings will be held to ensure you are successful and have a productive and enjoyable experience.

• Strong Python programming skills with production-level experience.
  
• Proven expertise in data engineering, building pipelines, integrating APIs, working with structured/unstructured data.
  
• Ability to thrive in high-ownership, startup-style environments with limited structure.
  
• Experience working across evolving requirements and ambiguous problem statements.
  
• Familiarity with cloud-based data tools and orchestration frameworks (e.g., Airflow, Prefect, DBT, Spark).
  
• Understanding of data modeling, schema design, and best practices for large-scale processing.
  
• Advanced English level.

• Experience in Fintech or handling financial data pipelines.
  
• Exposure to machine learning operations (MLOps) or supporting ML-driven systems.
• Familiarity with continuous data monitoring or audit-related products.

Jetpacks! is a digital accelerator. We help companies reach new heights, together, by committing to working alongside them, unlocking the power or LatAm.
We strive at creating connections between people, data and technology to realize connected outcomes across the full lifecycle of the product and platform ecosystems.

We’re makers, builders and creators by nature, and we come to work every day to build experiences for some of the world’s most influential companies. We help businesses accelerate their digital roadmap, rapidly innovate, modernize their systems, enable their teams and optimize for continued growth.

We welcome our team members to show up as their authentic selves every day. Because this is so important to us, Jetpacks! is proud to be an equal opportunity employer.