• You have taken a production Python service or pipeline through a significant change to its architecture — a re-model, a re-platform, or a rewrite of how data moves through it
• You design the data models and APIs other people build on, and you have lived with the consequences of your own schema decisions
• You work from a problem rather than a ticket: you pick the approach, make the call on the trade-offs, and can explain the reasoning afterwards
• You extend systems that already exist — including the parts nobody wants to touch — rather than reaching for a rewrite
• You use AI in your workflow, or are ready to, and you can explain what you kept, what you threw away, and why

Desirable

• Build the systems behind Treefera's Environmental Intelligence — the data models, pipelines and APIs that turn satellite and ground-truth signals into evidence customers can act on, fast enough to change a decision
• Ship services end to end — data model, pipeline, API — from a question a customer asked to something that answers it
• Turn emerging ideas into working prototypes quickly, so customer feedback arrives in weeks rather than quarters
• Own the technical decisions in your scope — extending Treefera's existing platform and its constraints, refactoring where it pays and resisting the rewrite where it doesn't
• Carry work past release through maintenance, documentation and operational follow-through, so what ships stays reliable
• Improve how the team builds through code review, mentoring less experienced engineers, and practical tooling improvements
• Land the work commercially — demo what you build and enable the people who sell and support it, so what you build gets adopted, not just shipped
• Within 30 days you will have shipped something small into production and know where the platform's edges and legacy corners are
• By 60 days you will own a piece of Environmental Intelligence end to end — data model through pipeline to API — including the problems that arrive as open questions rather than tickets
• By 90 days it is released and customers are querying it, sharpening the evidence organisations use to protect forests and de-risk supply chains
• By six months your work shows up beyond your pod, in the documentation, tooling and standards that make everyone quicker. Within a year, environmental evidence reaches the people who need it faster, and your work is a visible part of that
• You’ll join the Engineering team and partner day-to-day with Product, Customer Solutions and the Science/AI team, while working closely with HQ teams (Operations, Finance, Legal) and our enterprise customers

• Recruiter screen (30–45 min)
• Hiring manager & Collaborative technical session (45-60 min)
• Final cross-functional or executive conversation (If applicable). (30-45 min)

Salary benchmarks