Senior/ Expert Data Engineer

Main responsibilities:


Designs and implements the data pipelines and transformations necessary for our Data Sharing Platform.
Ensures quality and accuracy of data used by performing data quality measurement and analysis.
Works closely with Data Scientists, architects, and engineers to ensure that we produce high-quality code and infrastructure.
Maintains the high quality of our data pipelines in production, ensuring data quality and performance.
Stays current with rapidly developing data technologies and tools. Shares knowledge with others.
Implement strategies, standards, and best practices for data ingestion and integration.
Analyzes new sources of data to quantify quality, uniqueness, value, and overlap with existing data sources.
Involve to the platform governance process improvement.


Experience, Competencies and Skills Required:


Total work experience: Minimum 5 years.
Hands-on experience with SQL and NoSQL technologies.
Experience in Database Administration.
Programming proficiency in at least one of Python / SQL / PySpark.
Education: Bachelor’s degree in a relevant field.
Experience with data integration (ETL/ELT) concepts and tools.
Deep understanding of containers and Kubernetes.
Familiarity with DataOps practices and methodologies, with a strong interest in working in a highly collaborative environment.
Experience with continuous integration (CI) practices.
Ability to write, debug, unit test, and performance test data integration processes.
Ability to clearly define and address data quality issues.
Strong problem-solving and critical thinking skills.
Up-to-date knowledge of rapidly evolving data technologies and tools, with a willingness to share knowledge with others.


Candidates wishing to apply can send their CV to the e-mail address in the Apply for job button, specifying the job title in the “Subject” field. Only candidates who meet the requirements of the vacancy will be contacted for the next stage of the recruitment process.