Data Engineer

We are seeking a motivated and skilled Lead Data Engineer to guide a team of data engineers within our Data Science function and drive the development of innovative data solutions. You will lead engineering efforts on cutting-edge projects, collaborating with top experts in a dynamic, supportive environment.

As a key leader, you will mentor engineers, ensure high-quality data infrastructure, and contribute to impactful, data-driven initiatives that support business growth and scientific exploration. Join us and help shape the future of data engineering in an inspiring and collaborative setting! 

The main responsibilities of the position include:

• Employ state-of-the-art technologies for data architecture, storage, and processing. 

• Design, build, and maintain scalable and reliable data structures, pipelines and ETL processes using SQL/NoSQL and other relevant tools, to acquire and process large volumes of data from various sources. 

• Develop and maintain data warehouse, data lake and other relevant solutions to support a wide range of data requirements for the data science team. 

• Establish methodology for working with large-scale datasets practicing efficient aggregation and feature engineering. 

• Collaborate with cross-functional teams to define and enforce data governance policies and data security best practices. 

• Ensure data quality, integrity, and security by implementing appropriate data validation and monitoring techniques. 

• Identify and address performance bottlenecks in data processing and recommend optimizations to enhance system efficiency. 

• Troubleshoot and resolving issues related to data quality, data pipeline failures, and data infrastructure. 

• Research and stay up to date with emerging trends and technologies in the data engineering and data management field and recommend innovative solutions to enhance our data infrastructure. 

• Communicate results to the rest of the team and other departments. 

• Guide and mentor multiple teams, fostering innovation and technical excellence. 

• Present insights and model outcomes to non-technical stakeholders, translating data into actionable recommendations.

Main requirements:

• PhD or MSc in Data Science, Physics, Mathematics, Computer Science, or a related discipline. 

• 12+ years of professional experience in data science, with a strong emphasis on data engineering and fintech solutions. 

• Expertise in data warehousing and working with both relational and NoSQL databases (e.g., MongoDB). 

• Strong command of AWS services (MSK, Lambda, Glue, SageMaker) and infrastructure provisioning using Terraform. 

• Practical experience with cloud-native data platforms. 

• Familiarity with workflow orchestration tools such as Airflow or Kubeflow. 

• Experience implementing CI/CD pipelines using GitLab. 

• Advanced programming skills in Python, SQL, and at least one other high-level language. 

• Proficient in Unix/Linux environments. 

• Strong analytical and problem-solving abilities, with keen attention to detail. 

• Demonstrated success in leading data science or data engineering teams. 

• Effective collaborator in cross-functional, multi-stakeholder settings. 

• Excellent verbal and written communication skills in English. 

Benefit from:

• Attractive remuneration package

• Private health insurance

• Corporate pension fund

• Intellectually stimulating work environment

• Continuous personal development and international training opportunities