Data Infrastructure Engineer

Austin, TX or Remote within Continental US considered

Department:
Data Science

Reports to:

Head of Data Science

Location:

Austin, TX or Remote within Continental US considered

Applications will be open through February 2026, with an anticipated start date in March 2026.

Funga is a public benefit corporation harnessing forest fungal networks to address the climate crisis. We combine modern DNA sequencing and machine learning technology with breakthrough research on the forest microbiome to put the right native, biodiverse communities of mycorrhizal fungi in the right place. This leads to more quality wood created more quickly, more carbon sequestered, and more resilient forests.

We serve land partners seeking to implement regenerative forestry practices that improve productivity and sustainability, and corporate carbon buyers building high‑quality carbon removal portfolios with strong social and biodiversity outcomes. We’re a team of passionate scientists and builders on a mission to draw down at least three gigatons of carbon dioxide from the atmosphere by 2050.

If you are excited by starting new things, learning as you go, and being hands‑on in applying your work to the private sector, you will dig working with us. We encourage you to apply even if only some of the below criteria are met—just make sure to tell us why you’re excited about Funga!

At Funga, we leverage cutting‑edge data pipelines to manage large‑scale ecological, genomic, and geospatial datasets. We are looking for a Data Infrastructure Engineer to help us build scalable data solutions, streamline data ingestion, and maintain high‑quality databases that support our scientific and operational teams. This role will be instrumental in optimizing our data infrastructure, ensuring efficient data access, and supporting the broader team in making data‑driven decisions.

We are building a lean, high‑performance, low‑overhead stack built on open‑source foundations. You will be the primary architect of how Funga stores, moves, and accesses its data. This is a role for a builder who prefers simple, robust, accessible systems that are tailored to the teams who rely on them. This is a rare opportunity to have total technical ownership over the data systems that will scale our impact globally.

• Architect Core Systems & Cloud
  • Own the Stack:
    Architect and maintain our central storage (Postgre
    
    SQL/PostGIS, SQLite) and cloud environment (AWS/GCP), leveraging ECS, Lambda, and S3.
  • Modern Dev Ops:
    Standardize environments using Docker, CI/CD pipelines, and Infrastructure as Code to automate the testing and deployment of data services.
  • Scale for Performance:
    Optimize data models and database performance management for extensibility as our genomic and geospatial inputs scale.
• Manage the Data Lifecycle
  • Build Lean Ingest:
    Design and automate scalable ELT/ETL pipelines for genomic, geospatial, and tabular data from sources like Survey
    123, ArcGIS, and Asana.
  • QA/QC at Scale:
    Build automated validation pipelines to ensure data integrity and version control from the moment it hits our system.
• Enable the Mission
  • Internal Enablement:
    Support scientists and operational teams by designing the data models that power internal modeling workflows, dashboards, and reporting.
  • System Connectivity:
    Develop lightweight APIs and connectors to sync data between our core infrastructure and downstream applications (e.g. Asana, ArcGIS, and internal dashboards).

• 4+ years of experience in Data or Backend Engineering, with a track record of building production data systems from the ground up.
• Database expertise:
  Deep SQL proficiency. You understand indexing, partitioning, and optimizing Postgres for high performance.
• Cloud Infrastructure:
  Significant experience building, managing, and optimizing data services within AWS or GCP (e.g. ECS, Lambda, RDS) with a focus on cost‑effective, maintainable architecture.
• Modern Dev Ops & Python:
  Proficiency in production‑grade Python and modern Dev Ops practices, including containerization (Docker), CI/CD pipelines, and infrastructure monitoring.
• Data fluency:
  Experience handling large‑scale…