At a Glance
- Tasks: Lead a team to shape architecture for healthcare data solutions using Spark and AWS.
- Company: Join H1, a forward-thinking company revolutionising healthcare data management.
- Benefits: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving innovation in healthcare data.
- Why this job: Make a real impact in healthcare by improving data accuracy and efficiency.
- Qualifications: Experience in data engineering, cloud technologies, and team leadership required.
The predicted salary is between 60750 - 74250 £ per year.
H1 is seeking a Staff Data Engineer for the EMERALD team to shape architecture and scale for its healthcare entity resolution platform. You will lead a small team, stay hands-on, and own services powering automatching, identity mapping, grouping, deduplication, and enrichment across tens of millions of records.
You will collaborate with Product, AI/ML, Analytics, and Engineering to improve accuracy, reliability, and efficiency in a cloud-native environment using Spark, AWS, and modern infrastructure.
Staff Data Engineer — Spark & Healthcare Data (Remote) employer: h1
At H1, we pride ourselves on being an exceptional employer that champions health equity and innovation in the healthcare sector. Our inclusive work culture fosters collaboration and empowers employees to grow through meaningful engagement with leading biotech and life sciences companies. With generous benefits, flexible work arrangements, and a commitment to diversity, H1 offers a rewarding environment for those passionate about making a difference in healthcare.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Engineer — Spark & Healthcare Data (Remote)
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like h1!
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like h1.
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We think you need these skills to ace Staff Data Engineer — Spark & Healthcare Data (Remote)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at h1, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at h1. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at h1
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at h1!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
