Data Engineer (Healthcare Data)

at  Pangaea Data

As Data Engineer you will join Pangaea’s team to design and develop integrated applications for its PALLUX platform
LondonTechnical

TECHNICAL SKILLS:

• A university qualification (Bachelors, Masters, Doctorate) with at least two years of university study in Computer Science, Informatics, Data Science, Engineering, or related
• Experience in data engineering, with a focus on healthcare data preferred
• Familiarity with NoSQL databases (e.g., MongoDB) and relational databases (e.g., PostgreSQL, MySQL)
• 5+ years in Python and SQL work
• Knowledge of ETL tools (e.g., Apache Airflow) and cloud platforms (e.g., AWS, Azure, GCP).
• Understand data modelling concepts and best practices. Experience with healthcare data standards (e.g., HL7, FHIR, ICD, SNOMED, DICOM) preferred
• Excellent problem-solving and communication skills

THE ROLE

As Data Engineer (Healthcare Data), you will join Pangaea’s team to lead and support the development of reliable, scalable, and secure data solutions. The ideal candidate will be experienced with healthcare data standards (e.g. FHIR, OMOP), possess a strong understanding of data privacy regulations (e.g., HIPAA, GDPR), and have technical expertise to design and implement data pipelines, storage systems, and integrations.
This role will continue to evolve as the business grows, but in the short term it will also involve development of the software product and collaboration with the clinical and scientific team. A strong software engineering background and knowledge in AI, especially Machine Learning and Natural Language Processing, is essential. For the right candidate, this is a senior technical position with scope to grow into a leadership role.

KEY TECHNICAL RESPONSIBILITIES WILL INCLUDE:

• Design, implement, and maintain ETL pipelines to collect, clean, and transform healthcare data from various sources such as EHR systems, APIs, and databases
• Ensure data quality and integrity through robust testing and validation processes
• Optimize storage solutions for structured and unstructured healthcare data using databases (e.g., MongoDB) and cloud-based data warehouses (e.g., Azure Cosmos, Azure Fabric)
• Maintain strict compliance with data privacy regulations such as HIPAA, GDPR, and other local healthcare policies
• Work closely with the clinical team to understand data requirements and translate them into technical solutions
• Collaborate with the AI team to provide clean, well-structured datasets for research, and AI/ML models
• Stay up-to-date with the latest data engineering technologies and best practices