Senior Backend Product Engineer (Python) Valencia, Spain - Hybrid We are Datamaran: a fast-paced, energetic and high-growth technology company.
Datamaran is the only software analytics platform in the world that identifies and monitors external risks, including ESG.
Trusted by blue-chip companies and top-tier partners, it brings a data-driven business process for external risk and materiality analysis.
Our mission is to positively impact the world by helping corporations to have a robust sustainability strategy with our SaaS platform.
We recognize that people of different backgrounds widen our perspective, so we're committed to diversity, equality, and inclusion in everything we do.
Datamaran is proud to be an equal opportunity employer, and all applications received will be considered without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, or age.
The growing and dynamic Datamaran engineering team is looking for a seasoned Backend Python Developer with a T-shaped background, with expertise in Python's frameworks, such as FastAPI.
An appetite for machine learning (especially LLM like ChatGPT) will be a perfect match.
Responsibilities Design, build, and enhance Datamaran web applications and data processing pipelines.
Debug, deploy, and maintain large scale applications, from APIs to process pipelines.
Consider tradeoffs when designing and implementing features in backend systems.
Work closely with Frontend developers, Product managers, and other engineers in the Agile team to develop and implement new features.
Mentor developers on back-end development best practices and industry-standard engineering practices.
Stay informed of the latest industry standards and technologies, actively applying these to improve our products.
Contribute to product discovery phases, bringing invaluable insights regarding user needs and potential solutions.
A one thousand feet view of our tech stack: Our web application is built on node.js, javascript, and vue.js.
Our data stores include ElasticSearch and MongoDB, and we are evaluating bringing in SQL-based and vector databases.
Our server side and data pipelines are built in Python and FastAPI.
Everything is hosted on AWS, on EC2 or in lambda functions.
Our data pipelines are primarily centered around analyzing textual data, looking for patterns inside the narrative of long texts (Reports, international regulations, news articles, etc.).
Minimum Requirements: A Bachelor's degree in Computer Science or a related field.
5+ years of experience in backend development.
Mastery of Python, including common API frameworks (e.g., FastAPI) and libraries (e.g., pandas).
Some experience working in the frontend area and willingness to participate in frontend work when required.
Familiarity with AWS environment, as well as Unix/Linux.
Good understanding of development best practices, such as SOLID, testing, CI/CD.
Living within commutable range of Valencia and willing to work from the Datamaran hub regularly (typically once per week, but we will be flexible for the right candidate!).
Fluent in English.
Bonus Points: Experience in Vue.js or similar frontend framework.
Proven experience with Machine Learning tools in Python (pandas, spacy, langchain, etc.).
Knowledge of architecture concepts like MVC, CQRS, and DDD.
Experience with relational databases, as well as MongoDB and/or ElasticSearch.
Airflow (ideally version 2).
Data processing pipelines.
Compensation and Benefits: A highly competitive salary.
Flexible hours.
Hybrid working, with typically circa 3 days with the team in the Valencia hub.
11€ per day meal allowance + food and snacks at the office.
Private health.
Private pension (company doubles your saving).
Best equipment: choose between Mac or Linux.
Frequent training, budget for conferences, O'Reilly subscription.
Access to Urban Sports.
International environment (over 25 nationalities), with 50% of our leaders being women, and almost 50% of our tech team too.
Working in a climate-tech company, helping corporations to identify ESG risks.
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