Position: Middle Data Engineer for Fintech project
Company: Intellias
Category: Data Science
Experience required: 1y
English level: upper
Published: 2021-05-01T00:00:00+03:00

Science and Data sit at the heart of our client business and play a uniquely crucial role in what they do. With data, they build intelligent Real Estate Asset Management capabilities that help their Clients and Analysts to understand and maximize the return of their granular portfolios.

Fundamentally, data underpins the innovation and scaling of their current and future business at the Asset Management platform, and being part of the team gives you the chance to have a major impact across the company – apply today to join our client's world-class data science team.

**Responsibilities:**

You will be self-motivated and yearn for making an impact through your skills and determination.
You look for solutions to overcome problems, have strong analytical skills, and lead by example with high quality.
You demonstrate great attention to detail and effective communication skills.
You can work autonomously and take ownership. We thrive with space and responsibility to solve problems.
You approach work in a logical way. We are not afraid to make mistakes, but we use science, data, and logic to back up decisions and improve understanding.
You operate best without lots of bureaucracy. We don’t hide behind fancy job titles or clunky processes ‘because that’s how things are done.
And you share our mission to improve people’s relationships with their money.

**Requirements:**

Minimum 2-3 years of professional work experience as a data engineer on a Cloud Platform
Design data processing systems, such as batch ETL pipelines.
Build streaming data pipelines in a cloud.
Build and operationalize data processing systems (DB, warehouses, lakes)
Use cloud infrastructure to migrate existing MySQL workloads to cloud platform.
Employ big data warehouse and visualization tools to carry out interactive data analysis
Data modeling
Operationalize machine learning models