Data Engineer

Position is based in our London office or remotely in UK and Germany.

Please submit your CV in English

About the role:

You will be part of the Engineering team. This role involves designing, building, and optimizing scalable ETL/ELT pipelines with Airflow to process complex datasets efficiently while ensuring reliability and performance. You will organize and structure data systems, aligning them with business objectives, and demonstrate expertise in scientific and healthcare information systems to deliver data products tailored for machine learning and AI research. Clear reporting and meticulous attention to detail are essential, as is the ability to manage high-volume,  complex workstreams while prioritizing multiple deadlines. The role requires professional interpersonal skills to collaborate with diverse stakeholders in biotechnology and the ability to streamline production workflows for scientific processing and quality assurance.

• Organize and structure data systems at both macro and micro levels, designing and implementing data architectures that support business goalsOptimize data pipelines for performance, reliability, and scalability
• Design, build, and maintain scalable ETL/ELT pipelines with Airflow to process large-scale, complex datasets
• Demonstrate ability to delivery of of  data products  useful for machine learning and AI research and development (data models, metadata and semantics)
• Strong organizational skills to effectively manage high-volume, complex workstreams while prioritizing multiple deadline
• Demonstrate knowledge of scientific and healthcare information systems and data sources and relevant software tools
• Demonstrate ability to handle a variety of activities across operational delivery and development and initiatives
• Demonstrate professional interpersonal skills with ability to work both independently and collaboratively with a variety of stakeholders on complex biotechnology areas.
• Streamline the process of taking scientific processing and quality check in production, ensuring proper monitoring of the production workflows. 

In particular, you will:

• Design and optimizing data pipelines using Airflow
• Develop robust solutions in Python and SQL
• Design, develop, and operate scalable ETL/ELT pipelines to process and transform datasets.
• Work with cross-functional teams, including data scientists, business developers, software engineers and bio medical researchers to deliver high-quality data solutions.
• Manage and monitor containerized data infrastructures with Docker and Kubernetes and other cloud platforms.
• Implement and enforce best practices for data governance, security, and compliance.
• Build, optimize and maintain data architectures, including data lakes, data warehouses, and analytical Insights 
• Productionize the data processing pipelines, setting and enforcing standards and best practices across scientific teams to deliver high quality data in an efficient and scalable way.

 

About you

Required qualifications / experience:

• Master degree in computer sciences or specialization in Data 
• Significant experience (5+ years) as a Data Engineer and have good knowledge of DataOps practices.
• Experience in Python and SQL and you have familiarity with R
• Experience in architectural design of complex data platforms
• Proficient in the technologies like Airflow, AWS steps functions, PostgreSQL, Docker, Kubernetes, Grafana, Infrastructure as Code
• Autonomous, meticulous, and enjoy teamwork
• Software development with a focus on code quality, simplicity, maintainability
• Experience in designing data architecture and building data products
• Experience handling sensitive personal information
• Fluent in English

Preferred qualifications/bonus:

• Knowledge in healthcare or biology areas
• Data quality tools: Great expectation, pydantic, pandera, SQLMesh etc,  
• Debugging & Refactoring skills

 

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