(Senior) Data Engineer/MLOps

Machine Learning (ML) is revolutionizing the way of doing business at a global scale. In business lending, Finiata takes the technological forefront by developing proprietary technology that allows us to take accurate decisions in a fully data driven fashion. YOU will contribute to further develop the in-house all-data-things technology by engineering and productizing novel pipelines and ML models.

Note: This position is fully remote as long as you are legally based in Germany, Poland, Portugal, Italy or Romania. You may be required to travel for business purposes (e.g.: participation in team building activities, professional workshops) up to 10% of the time.

You will:

• Work closely with Data Scientists, Backend Engineers, Quality Engineers and DevOps to operationalize proprietary machine learning technology for different problems
• Design and maintain scalable ETL and MLOps infrastructure usable in multiple scenarios and applications (e.g.: data science, advanced analytics)
• Design and develop health and performance monitoring tools (MLOps) of data pipelines and the  machine learning services in production
• Design and improve heterogenous, asynchronous and high-performance large-data processing pipelines from/to multiple sources/destinations

• Operationalize innovative, data-intensive, end-to-end machine-learning(ML)-based decision engines

• Highly motivated with excellent communication and strong interpersonal skills
• In-depth knowledge and professional working experience with software engineering, ETL pipelines and setting up machine learning workflows
• Proficiency in Python
• Experience in implementing and deploying REST microservices and Kafka messaging queues in AWS cloud ecosystem
• Basic understanding of data science project lifecycles and commonly associated RDBMS/NoSQL technologies
• Fluent written and verbal communication in English

As a plus:

• 2+ years of experience in deploying and maintaining in production data pipelines working at scale which are fuelling and/or being fueled by machine learning models in production
• Basic understanding of machine learning product lifecycle and the commonly associated components (MLOps): Experimental Environment (e.g.: Python scikit learn, Jupyter Notebook) Workflow management (e.g.: MLFlow), Feature Stores (e.g.: Feast), DataOps/Pipelines (e.g.: Kafka), Model Deployment (e.g.: Terraform), Testing, Serving (e.g.: Docker, Flask). and Monitoring (e.g.: Datadog), Model Repository (e.g.: DVC) *

* List of technologies/methodologies is for illustrative purposes. You are not expected to have experience in each single one of these technologies/methodologies. We don’t believe in super-heroes but rather in super-teams ?

• Culture of trust, constructive feedback and self-organization, agile mindset, regular face-to-face team building events and regular knowledge sharing (E.g.: through tech talks , including invited keynotes as well)
• Be paid a high competitive compensation (at Central European standards) that recognizes your talent – without excuses, vouchers or other shortcuts. Just a fair salary for YOU
• Get to make a real impact on thousands of small businesses every day, contributing for more equal and inclusive economy around the globe
• Work with the best and learn from other competent and brilliant people
• Get access to our Internal Tech Academy – where the company invests on your continuous training and professional growth (individual growth plan, internal top-flight coaches, paid conferences/courses/learning materials, dedicated working time for learning purposes)
• Be supported to grow and take leadership from day one
• Enjoy 24 days of paid holidays
• Benefit from flexible working hours and additional Company Holidays on 24th and 31st December
• Possibility of participating in our company equity program (senior level-above)

Check out our StackShare.

Check out our blog.

Finiata is a technology provider that enables small businesses to focus on what matters most: their business. As a data-first organisation, we wake up everyday to challenge the established practices in the B2B Fintech landscape. We do it by building cutting-edge AI technology in-house that enables us to personalise profitable lending offers at scale and in real-time.