Enveritas is a 501(c)3 non-profit and Y Combinator-backed startup looking to hire for our Data Team. You can learn more about this role and our Data Team at https://www.enveritas.org/jobs/data-eng/
Our Data Team creates models, analysis, and visualizations to better understand our data about the climate, economic, and social conditions experienced by coffee farmers. We write code to transform raw survey data into insights that match our sustainability standards.
Out stack in the Data Team relies mostly on Python, Postgres, AWS, and Looker.
Building and refactoring tools to improve the efficiency of our tools for our Country Operations teams. You will identify opportunities for improving our current workflows and our codebase. This will include building automated workflows using Python and refactoring existing code for robustness and quality.
Improving the developer experience for our data analysts. You will be in charge of our Github repositories and AWS instances. This includes managing the build environments, maintaining our AWS instances, and helping us with best coding practices in code reviews.
Maintaining and upgrading our data pipeline. You will own our data pipeline / ETL and will be responsible for improving it. The pipeline is written in Python, currently runs on a single EC2 instance, and writes its output to a PostgreSQL database.
Qualifications
- A degree in computer science, or an equivalent training on the principles of software engineering.
- Multiple years of professional experience using Python and SQL in a team environment.
- Fluency with Linux and command-line tools (terminal/bash, git, cron, make).
- Excellent communication and analytical skills; flexible problem-solving attitude.
- Advanced spoken and written English required.
- An excitement for our mission of improving the lives of smallholder farmers and an interest in sustainability.
Research shows that people of different backgrounds read job postings differently. If you don’t think you meet all of the qualifications but do think you’d be a great match for us, please consider applying and sharing more in your cover letter. We’d love to talk with you to see what skills you can bring to our team. This said, we are most likely to be interested in your candidacy if you can demonstrate the majority of the qualifications listed above.
Our team is fully distributed, so you should be comfortable with remote work. This role is a full-time individual contributor role. While you can be located anywhere, our core hours are 10am to 2pm Eastern Time (currently UTC -4) Monday through Friday, with team members choosing either an early start or later stop as suits them.
Our work is often ambiguous, so you should have a love for environments with uncertainty. Most of our work is internal facing, so our product specs are often rough. For this role, you will be the only engineer on our Data Team (and supported by engineers on our Engineering Team), so you should be comfortable working with data analysts to write software and review others’ code. You should have a deep empathy for users of our tools and understand the importance of supporting the work of other teams.
The base salary for this position will be between $125,000 and $140,000 annually. For the US, this is a full-time exempt position. In the US, full benefits include 401k with matching contributions, Medical/Dental/Vision, and Flexible Spending Account (FSA), 4 weeks vacation in addition to public holidays, and personal/sick time.
For a hire outside the US, the specific benefits and compensation details will vary as required to account for your region’s laws and requirements. Salary for this position will be paid in relevant local currency.
For all staff, we are able to offer:
• Annual education budget for conferences, books, and other professional development opportunities.
• Annual all-company retreat (as Covid and other travel restrictions allow).
• Field visits to our Country Ops teams in coffee-growing countries such as Colombia, Costa Rica, Ethiopia, and Indonesia.
Fully remote
Candidates can reside anywhere in the world.
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