Job description

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As Trase enters an exciting new phase with a strategy for 2021–2025 to mainstream the deployment and uptake of data, SEI HQ is recruiting a highly motivated early career data engineer with a strong interest in sustainability, particularly linked to the environmental and social impacts of commodity production, trade and consumption.
Location: Stockholm, Sweden
Deadline: 25 October 2021
Length of contract: Fixed-term (3 years) with possibility of renewal
Start date: ASAP
Join our international non-profit research organization and help create a sustainable and prosperous future for all! SEI HQ is a dynamic and expanding workplace that employs around 110 people from 28 different nationalities in an activity-based office in central Stockholm (Garnisonen), with an additional 200 employees in centres around the world.
Trase (Transparency for Sustainable Economies) is a pioneering sustainability data and intelligence initiative that reveals the connections between consumers, producers and investors, as well as the environmental and social impacts linked to global supply chains. The Trase approach draws on vast sets of production, trade, customs and financial data, for the first time laying bare the flows of globally traded commodities – such as palm oil, soya and beef – at scale, as well as the flows of capital used to finance this trade. Trase is a direct response to the ambitious commitments made by leaders across sectors to achieve deforestation-free supply chains – and the urgent need this creates for a breakthrough in assessing and monitoring sustainability performance. Trase is jointly led by SEI and Global Canopy with many additional partners and close collaborators. The Trase team is made up of over 30 individuals, located in nine countries, brought together by enthusiasm, curiosity and drive.
The role
You will be part of a leading, multinational, multidisciplinary and multilingual team of experts, working across the Trase initiative. You will work as a key member of the Trase Data Observatory – which focuses on democratizing access to the Trase data – by helping model, analyse and query Trase data, as well as providing tools that can improve how target users access and engage with Trase data and actionable insights. You will also play a supporting role in the Trase Data Tools team focused on maintaining the Trase master database and pipeline for processing trade and supply chain data. We value diversity, inclusivity and creativity at the core of what we do and we welcome applicants from diverse backgrounds to apply.
Main responsibilities
Work with Trase data scientists to improve access to Trase data by building and maintaining targeted tools and interfaces that enable better external and internal access to and understanding of the full extent of Trase data, including through data modeling, automating data reports and creating API end points
Support the prototyping of new features and functionality for the public offering of Trase, including bringing some of this work to production
Support maintenance of Trase database and Trase data pipeline
Improve data governance by supporting the development of an internal data catalog
Work closely with colleagues across the Trase partnership, including at SEI and co-founder Global Canopy in the UK to facilitate data access and develop greater data literacy and understanding
Coordinate with other colleagues in SEI, as well as in collaborating institutions, including our partner institute Global Canopy in the UK, in working on these tasks.

Who you are
You should have a strong interest in using your data engineering skills to support research on the major environmental and sustainability challenges the world faces in the 21st century.
Key qualifications
Master’s degree or equivalent experience, and at least one year of work experience
Experience with relational database management, modeling and querying
Experience with data pipelines and ETL/ELT
Solid SQL knowledge
Intermediate knowledge of Python
Strong strategic and analytical thinking
Experience with cloud service platforms for data processing (Amazon Web Services; AWS or Google Cloud Platform, with preference for AWS)
Good software engineering practices
Git and agile development practices
Fluency in English.

Desirable qualifications
Experience with Metabase
Experience with PostgreSQL
Experience with workflow management systems (Apache Airflow, Luigi)
Experience with container tools (Docker, Kubernetes)
Experience with data modeling, maintenance, and governance in a Data Warehouse
An understanding of modern CD/CI
Experience working in research and/or civil society organizations
Experience working in multicultural and multilingual teams.

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