Data Engineer (Healthcare Data)
Data Engineer (Healthcare Data)

Data Engineer (Healthcare Data)

London Full-Time 43200 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and develop data solutions for healthcare applications on the PALLUX platform.
  • Company: Pangaea is a pioneering healthcare data company with a focus on AI-driven solutions.
  • Benefits: Enjoy private medical insurance, a monthly travel card, and opportunities for professional growth.
  • Why this job: Join a renowned team and make a real impact in healthcare through innovative data engineering.
  • Qualifications: A degree in Computer Science or related field, with experience in healthcare data engineering preferred.
  • Other info: Opportunity to learn from experienced professionals and grow into a leadership role.

The predicted salary is between 43200 - 72000 £ per year.

As Data Engineer, you will join Pangaea’s team to design and develop integrated applications for its PALLUX platform. Pangaea is a South San Francisco and London based business founded by Dr Vibhor Gupta and Prof Yike Guo. They have worked in medicine and computing for over 20 years and have raised over $300 million through their academic research, including a $110 million grant focused on development work on large language models in medicine. Pangaea’s AI platform, PALLUX, is configured on clinical guidelines to find more untreated (undiagnosed, miscoded, at-risk) and under-treated patients with hard-to-diagnose conditions for screening and treatment at the point of care.

The Role: As Data Engineer (Healthcare Data), you will 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.

Mandatory Requirements:

  • A university qualification (Bachelors, Masters, Doctorate) with at least two years of university study in Computer Science, Informatics, Data Science, Engineering, or related fields.
  • 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.
  • Ability to communicate complex ideas effectively, both verbally and in writing.
  • Ability to engage all levels of the company and the customers’ organizations.
  • Ability to work collaboratively in a team environment.

Nice to Have:

  • 3-5 years experience of managing teams.
  • Experience working on large-scale, commercial software development projects is a plus.
  • Experience with research communities and/or efforts, including having published papers (being listed as author) at AI/ML/NLP/CV conferences and journals.
  • Experience and knowledge of deploying AI and Data solutions for healthcare and pharmaceuticals at scale is desirable.

Perks and Benefits:

  • Salary dependent on experience.
  • Package of attractive benefits including private medical insurance and monthly travel card.
  • You will join a dedicated highly renowned team offering you the opportunity to grow and develop your professional skills and profile.
  • You will have the opportunity to learn about building a startup business from experienced professionals and serial entrepreneurs.

Application Contact Information: Your application should include a CV and cover letter highlighting your relevant experiences and motivations. Please send this to careers@pangaeadata.ai.

General Information: Pangaea Data is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics protected by local laws, regulations, or ordinances.

Data Engineer (Healthcare Data) employer: Pangaea Data Limited

Pangaea is an exceptional employer, offering a dynamic work environment in London where innovation meets healthcare. Employees benefit from a comprehensive package that includes private medical insurance and a monthly travel card, alongside opportunities for professional growth within a renowned team of experts. With a strong focus on collaboration and cutting-edge technology, Pangaea empowers its staff to contribute meaningfully to the development of AI solutions that enhance patient care.
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Contact Detail:

Pangaea Data Limited Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineer (Healthcare Data)

✨Tip Number 1

Familiarise yourself with healthcare data standards like FHIR and OMOP. Understanding these standards will not only help you in interviews but also demonstrate your commitment to the role and the industry.

✨Tip Number 2

Network with professionals in the healthcare data field, especially those who have experience with AI and machine learning. Engaging with industry experts can provide insights into the role and may even lead to referrals.

✨Tip Number 3

Stay updated on the latest trends in data engineering and healthcare technology. Being knowledgeable about current advancements will allow you to speak confidently about how you can contribute to Pangaea’s mission.

✨Tip Number 4

Prepare to discuss your experience with ETL processes and cloud platforms during the interview. Be ready to share specific examples of how you've implemented data solutions in previous roles, as this will showcase your technical expertise.

We think you need these skills to ace Data Engineer (Healthcare Data)

Data Engineering
Healthcare Data Standards (e.g. FHIR, OMOP)
Data Privacy Regulations (e.g., HIPAA, GDPR)
ETL Pipeline Design and Implementation
Data Quality Assurance
Database Management (e.g., MongoDB, PostgreSQL, MySQL)
Cloud Platforms (e.g., AWS, Azure, GCP)
Python Programming
SQL Proficiency
Data Modelling Concepts
Communication Skills
Problem-Solving Skills
Collaboration in Team Environments
Knowledge of AI/ML Technologies
Experience with NoSQL Databases

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experiences in data engineering, especially with healthcare data. Emphasise your familiarity with standards like FHIR and OMOP, as well as your technical skills in Python and SQL.

Craft a Compelling Cover Letter: In your cover letter, express your motivation for applying to Pangaea and how your background aligns with their mission. Mention specific projects or experiences that demonstrate your expertise in data pipelines and compliance with data privacy regulations.

Showcase Technical Skills: Clearly outline your technical skills related to ETL tools, cloud platforms, and database management. Provide examples of how you've implemented these skills in previous roles, particularly in healthcare settings.

Highlight Collaboration Experience: Since the role involves working closely with clinical and AI teams, mention any past experiences where you collaborated with cross-functional teams. This will show your ability to communicate complex ideas effectively and work in a team environment.

How to prepare for a job interview at Pangaea Data Limited

✨Understand Healthcare Data Standards

Make sure you have a solid grasp of healthcare data standards like FHIR and OMOP. Be prepared to discuss how you've applied these standards in your previous work, as this will show your relevance to the role.

✨Showcase Your Technical Skills

Highlight your experience with Python, SQL, and ETL tools like Apache Airflow. Be ready to provide examples of data pipelines you've designed or optimised, as technical expertise is crucial for this position.

✨Communicate Effectively

Since you'll be collaborating with clinical teams, practice explaining complex technical concepts in simple terms. This will demonstrate your ability to engage with non-technical stakeholders and ensure everyone is on the same page.

✨Stay Updated on Industry Trends

Research the latest advancements in data engineering and AI, particularly in healthcare. Being knowledgeable about current trends will not only impress your interviewers but also show your commitment to continuous learning in this rapidly evolving field.

Data Engineer (Healthcare Data)
Pangaea Data Limited
Location: London
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