Join us in one of the hottest startups in Spain, breaking into a new market worldwide, learning and contributing with your expertise in innovating the entire job market!
Be the main referent of our Python code, help to raise the quality bar of any Python code we use.
We use Airflow as our ETL, a very powerful Python framework that allows us to break down any complex problem/process into smaller ones. Each component can be implemented directly in Python, or in any other language since they could be docker images executed in ECS instances.
The main priority is a senior profile with extremely solid Python skills, previous experience with Data/ETL is nice-to-have but it is not mandatory.
Overall, we can resume the main responsibilities as follow:
- Raise the level of our Python good practices, code structure, cleaning, and testing.
- Design and implement high-quality and performant Python code within our powerful ETL.
- Automate external integrations with our Data Lake and Data Warehouse.
- Automate complex solutions that might require to train, build, and deploy a series of Machine Learning algorithms (no previous experience with ML required).
In addition, we are looking for a senior profile that could be interested in:
- Mentor mid- and junior- Python Engineer: given the great impact of our ETL on the entire company, we want to grow a team dedicated to it, capable of improving, maintaining, and boosting it even further.
- Sharing her/his knowledge inside and outside Jobandtalent, raising the quality standards of the entire team with the aim of growing together.
- Contributing to Open Source projects: we are using different Open Source frameworks and libraries, and one of our wishes would be to contribute to some of those projects, dedicating part of our time when possible.
Requirements and Skills
- Bachelor’s degree in Math, Engineering, Stats, or Quantitative field.
- 4+ years of proven experience programming in Python with production-ready code (not scripting code).
- Extremely skilled programmer (e.g., unittest, production/staging experience).
- Experience with
- Different kinds of standard databases (e.g., RDBMS, NoSQL).
- Container development with Docker or Kubernetes.
- The leadership of projects, services, or products.
- Excellent verbal and written communication skills; ability to communicate effectively with different levels of management, as well as the business and technical communities.
- (Nice to have) Previous experience with
- ETL, data pre-processing, or data analysis.
- Supervising junior and mid-level developers.
- Experience with Big-data frameworks and OLAP DBs
- Stream processing framework (e.g., RabbitMQ, Kafka, Spark, Flink).
- Fluent in English is a must.
Examples of Projects and Responsibilities
- You receive a Jupyter Notebook made by one of our Data Analysts which contained a prototype of a data processing pipeline that generate very important data for our stakeholder. The Data Analyst has previously confirmed the data is corrected, but the code is definitely not ready for production. You need to understand it, define which is the best way to automate it (Airflow Python DAG, using Spark, external tools, etc.), and start the implementation by yourself or together with other team members.
- The previous example works in a similar way for Data Scientists when they come requesting help with automation about how to train a Machine Learning model that we want to re-evaluate on a weekly basis. Ideally, we want the results of the evaluation to be automatically computed and shared via a Slack channel, so we can quickly review them and decide if the model can be moved to production.
- We are expecting you to raise the quality bar of our code: helping your team members understanding which is the best way to structure the code for a specific problem, defining better protocols, introducing metrics when they are missing, improve the code performance, etc.
Offer in Short
- Great ownership of the projects with a direct impact on the product.
- Competitive Salary
- Transparent Equity package.
- Discount on Health insurance.
- A yearly budget for Conferences/meetup/self-learning.
- Working in an international and multidisciplinary team
You will be working in the Data Science team (read the last blog posts), together with Full-stack Engineers, Data Scientists, and Data Analysts.