Role Overview:
We are seeking an experienced
Data Engineer
to join a dynamic biotech company based in the USA (working in PT timezone). In this role, you will be responsible for designing, building, and optimising scalable data solutions that support the organisation's analytical and operational needs. You will work on developing data pipelines, implementing data quality checks, and ensuring robust data management systems. Domain expertise in biological or scientific data is highly advantageous.
Key Responsibilities:
- Design, build, and maintain ETL/ELT pipelines to process and transform data efficiently.
- Develop and optimise scalable data architectures in the cloud (preferably GCP).
- Implement and maintain data cataloging solutions to ensure data discoverability and governance.
- Build APIs and integrations for seamless data exchange across systems.
- Perform data quality checks and implement automated testing frameworks to ensure data accuracy and reliability.
- Collaborate with teams to build self-service systems and promote data democratisation .
- Document and maintain data engineering processes and best practices.
Qualifications:
- Strong experience in data engineering and cloud platforms (preferably GCP).
- Proficiency in Python , SQL , and shell scripting .
- Familiarity with data catalog tools (e.g., DataHub, Apache Atlas) and metadata management .
- Experience with building and maintaining scalable ETL pipelines using orchestration tools like Dagster or Airflow .
- Understanding of API development and integration.
- Knowledge of data governance and data quality principles.
- Background in biological or scientific data is a plus but not mandatory. Domain expertise can substitute formal education.
- Strong problem-solving skills and ability to work with cross-functional teams.
- Excellent communication skills in English, both written and verbal.