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- Tasks: Design and implement ETL pipelines for healthcare data using Python and SQL.
- Company: Join an AI-driven healthcare company focused on improving health outcomes and reducing inequalities.
- Benefits: Enjoy flexible working options and the chance to make a real impact in healthcare.
- Why this job: Be part of a mission-driven team that values innovation and collaboration in healthcare.
- Qualifications: Experience with Python, SQL, and cloud-based tools is essential; passion for data is a must.
- Other info: Contribute to compliance with ISO standards while enhancing your data engineering skills.
The predicted salary is between 36000 - 60000 £ per year.
I’m working with an AI-driven healthcare company who use AI-powered tools and proactive clinical coaching to improve health outcomes, reduce health inequalities, and create a more personalised care experience.
We’re looking for a Data Engineer to support the development and maintenance of healthcare data pipelines and platforms, with a strong emphasis on building robust ETL processes and scalable data architectures.
Key responsibilities:
- Design and implement ETL pipelines for healthcare data using Python, SQL,
and cloud-based tools
- Develop and maintain data infrastructure on Azure including data lakes,
warehouses, and processing frameworks
- Create robust data transformation processes ensuring data quality,
consistency, and security
- Implement orchestration to automate manual workflows such that they are
reliable, repeatable, secure and robust
- Collaborate with Data Science and Clinical teams to understand data
requirements and deliver actionable insights
- Apply security-first practices in all data processing solutions to protect
sensitive patient information
- Contribute to team knowledge through documentation and sharing of data
engineering best practices
- Help maintain compliance with ISO27001 and ISO13485 requirements for
healthcare data management
- Participate in architectural planning to improve overall data infrastructure
and capabilities
Data Engineer employer: Hlx Life Sciences
Contact Detail:
Hlx Life Sciences Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as Python, SQL, and Azure. Having hands-on experience or projects that showcase your skills in these areas will make you stand out.
✨Tip Number 2
Network with professionals in the healthcare data engineering field. Attend relevant meetups or webinars to connect with others who work in AI-driven healthcare, as they may provide insights or even referrals for opportunities at our company.
✨Tip Number 3
Demonstrate your understanding of data security practices, especially in relation to healthcare data management. Be prepared to discuss how you would implement security-first practices in your data processing solutions during interviews.
✨Tip Number 4
Showcase your ability to collaborate effectively with cross-functional teams. Prepare examples of past experiences where you worked with data scientists or clinical teams to deliver actionable insights, as this is a key aspect of the role.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Data Engineer in a healthcare context. Familiarise yourself with ETL processes, data pipelines, and the specific technologies mentioned, such as Python, SQL, and Azure.
Tailor Your CV: Highlight your relevant experience in data engineering, particularly any work with healthcare data or similar industries. Emphasise your skills in building ETL pipelines and maintaining data infrastructure, ensuring to mention specific tools and technologies you've used.
Craft a Compelling Cover Letter: In your cover letter, express your passion for using data to improve health outcomes. Discuss how your background aligns with the company's mission and how you can contribute to their goals, particularly in terms of data quality and security.
Showcase Your Projects: If you have worked on relevant projects, include them in your application. Describe your role, the technologies you used, and the impact of your work. This will demonstrate your practical experience and problem-solving abilities in real-world scenarios.
How to prepare for a job interview at Hlx Life Sciences
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and cloud-based tools like Azure. Highlight specific projects where you've designed and implemented ETL pipelines, as this will demonstrate your hands-on expertise.
✨Understand Healthcare Data Challenges
Familiarise yourself with the unique challenges of handling healthcare data, such as compliance with regulations like ISO27001 and ISO13485. Showing that you understand these complexities will set you apart from other candidates.
✨Emphasise Collaboration
Since the role involves working closely with Data Science and Clinical teams, be ready to discuss how you've successfully collaborated in the past. Share examples of how you’ve gathered requirements and delivered actionable insights through teamwork.
✨Demonstrate a Security-First Mindset
Given the sensitive nature of healthcare data, it's crucial to convey your commitment to data security. Discuss any practices or frameworks you've implemented to ensure data quality, consistency, and security in your previous roles.