- Location: Based in LATAM with Ocassional Travel
- Department: Operations & Technology
- Reports to: Data Products Lead
- Works closely with: Field Data Engineers, Science & Monitoring, Restoration Scope, project teams (Panama, Mexico)
- Part-Time Role

About Ponterra

Ponterra is a developer and operator of biodiverse carbon projects on degraded cattle ranching lands in Panama and Mexico. Our vision is to develop nature at scale in partnership with local communities. Our high-quality, high-integrity projects integrate sustainable land and livestock management practices with biodiverse restoration.

Role Overview

We are seeking a Data Engineer to build and maintain the data pipelines that connect project-level data systems into a shared structure supporting land acquisition, restoration, MRV (Monitoring, Reporting, and Verification), compliance, and decision‑making.

This role focuses on structuring and standardizing data across projects (e.g. Panama, Mexico and other Latin American countries), transforming fragmented inputs into a coherent system that supports carbon accounting, auditability, and internal + investor reporting.

The Data Engineer will work closely with project‑level Field Data Engineers (who manage data capture systems) and in the future a Data Manager (who will define structure), and will play a central role in developing Ponterra’s “data bus” -a lightweight but scalable backbone connecting multiple projects into a unified system.

Key Responsibilities

- Data Pipeline Development:



Build and maintain ingestion pipelines from multiple data sources, including spreadsheets (Panama, Mexico) and new project data as needed. Ensure reliable and scalable data flows across projects.
- Data Standardization and Transformation: Structure and transform incoming data into a shared schema (e.g. parcels, interventions, measurements, evidence), enabling consistency across projects and use cases.
- Data Bus Development: Develop and maintain a lightweight “data bus” that connects multiple projects into a unified system, enabling cross‑project visibility and standardization.
- System Integration: Work closely with project‑level Field Data Engineers to ensure alignment between data capture systems and downstream data structures. Support integration with project operations SaaS platforms like Restoration Scope and other tools as needed.
- Support for Land Acquisition, Restoration, MRV and Compliance: Ensure that data pipelines support traceability from raw data to claims (e.g. leakage, carbon accounting), including evidence structuring for audit readiness.
- Internal Reporting and Modeling Support: Enable downstream use cases including carbon modeling inputs, internal reporting, and investor‑facing outputs.





What Success Looks Like (First 3 to 6 Months)

- Panama project data mapped from spreadsheets into a consistent, usable structure
- One new project onboarded cleanly from day one
- Core data model (parcels, interventions, measurements, evidence) established and in use
- Key compliance use cases (e.g. evidence traceability) supported end‑to‑end
- Basic outputs available for upcoming internal and investor reporting milestones

Qualifications

- Technical Proficiency: Strong experience in data engineering (Python, SQL, pipeline development). Experience building and maintaining data ingestion and transformation workflows.
- Practical Data Experience: Comfortable working with messy, real‑world datasets and evolving systems. Able to move quickly without over‑engineering.
- Systems Thinking: Ability to design scalable data structures that support multiple use cases (MRV, reporting, modeling) across projects.
- Collaboration: Strong ability to work cross‑functionally with technical and non‑technical teams, including Field Data Engineers and project operators.
- Communication: Able to explain data structures and system logic clearly to stakeholders across teams.
- Language: English and Spanish required.
- Bonus: Experience with geospatial or environmental data systems.

Education

Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. Relevant experience may substitute for formal education.

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📌 Data Engineer (Ciudad de México)
🏢 Ponterra
📍 Ciudad de México