Data Engineer

Global Canopy is a data-driven not for profit that targets the market forces destroying nature.
We do this by improving transparency and accountability. We provide innovative open-access
data, clear metrics, and actionable insights to leading companies, financial institutions,
governments and campaigning organisations worldwide.

Corporate Performance: A growing number of companies and financial institutions are seeking to
mitigate their impacts on nature. But many have made commitments that are not being met, and
others are failing to take any action at all. Through our Corporate Performance work and Forest
500 project, we assess the policies and performance of influential companies and financial
institutions. Our newly launched Deforestation Action Tracker monitors financial institutions
with significant climate commitments to track their action on deforestation and associated
human rights abuses.

We also support financial institutions and investors by providing a suite of guidance including
our Deforestation-free finance Roadmap, Pensions Guidance and our Deforestation-free investment
mandate. And we support the finance sector, policy makers and other stakeholders by providing
market-leading data on deforestation and ESG metrics through our Forest IQ project.

Role overview

Global Canopy is seeking a hands-on Data Engineer to help modernise and automate our data
platform as we scale. As well as performing data uploads, data cleaning and other routine tasks
using existing methods, you will suggest and implement improvements to make these tasks more
straightforward and robust. You will be well versed in best practices for data engineering and
will be comfortable following industry-standard development processes.

Our data is complex and text-heavy, with both internal and third-party data sources. We are
aiming to reduce the number of manual interventions required in its processing and make our
systems more reliable and efficient. Tasks you will be involved with include:

• Building data pipelines using appropriate tooling.
• Adding new and altering existing cloud data infrastructure.
• Creating automated CI/CD pipelines.
• Fixing issues found in the data, and implementing checks to ensure they don’t recur.

Key requirements

To be successful in this role, these are the things that will matter the most:

• Experience building robust ETL pipelines.
• Experience working with common cloud data engineering tools.
• Strong SQL and python skills.

Essential behavioural competencies:

• Engaging and developing good working relationships with multiple stakeholders.
• Attention to detail and quality.
• A problem-solving approach and ability to identify opportunities to improve data systems.
• Good organisational skills and ability to manage a varied workload.

Preferred tech stack:

• SQL (ideally Postgres)
• Python (including pandas)
• R
• Terraform for infrastructure as code
• Git for source control
• GitHub actions for CI/CD
• Cloud infrastructure (ideally AWS)
• Airflow or other pipeline orchestration tool
• dbt or other transformation tool

At Global Canopy, we value diversity and inclusion. You can read our diversity statement on our
website. We encourage applications from all backgrounds and are committed to having a team with
a diverse set of skills, experiences and abilities. We are committed to reducing systemic
barriers in our recruitment processes.

Global Canopy works on issues of tropical deforestation. We are particularly interested in
strengthening our team to include those with a background from forest regions such as Latin
America and South East Asia. We welcome applications from people from these regions.

Global Canopy is an inclusive employer and accommodations will be made to allow anyone who
requires additional support to apply for this role. Please get in touch with us if you require
any additional support.