At Sensyne Health we combine technology and ethically sourced patient data to help people everywhere get better care. To do this, we have created a unique partnership with the NHS that delivers a return to our partner Trusts and unlocks the value of clinical data for research while safeguarding patient privacy. Alongside this, we develop clinically validated software applications that create clinician and patient benefit while providing highly curated data. Our products include vital-signs monitoring in hospitals and patient-to-clinician apps to support self-care and remote monitoring of gestational diabetes and chronic diseases such as COPD and heart failure.
We use our proprietary clinical AI technology to analyse ethically sourced, clinically curated, anonymised patient data to solve serious unmet medical needs across a wide range of therapeutic areas, enabling a new approach to clinical trial design, drug discovery, development and post-marketing surveillance.
As a Data Engineer, you will be responsible for building and optimising our data architecture and pipelines, as well as data flow and data collection for cross functional teams. You’ll be supporting our Digital Health and Clinical AI research teams carrying out data sourcing, data wrangling and feature engineering tasks. Working with other analysts, you will deliver clean and consistent data pipelines for our teams across the business and with external partners. This role brings exciting opportunities to design and optimise our company’s data architectures and tech stack to bring life to our next generation of products and data analysis, including the chance to work on truly big data initiatives in health data and genomics.
- Create and maintain an optimal data pipeline architecture and data warehousing in a greenfield environment.
- Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using big data technologies.
- Work to deliver configurable, scalable, reliable tools in the form of infrastructure-as-code solutions.
- Qualified to BSc level in Computer Science, Software Engineering or other relevant quantitative discipline, or equivalent.
- Extensive practical knowledge of multiple database architectures (SQL, noSQL, graph databases).
- Experience architecting and optimising ‘big data’ data pipelines and warehousing / data lakes with leading edge tooling (e.g. the Hadoop/Apache ecosystem, data warehousing technologies, etc).
- A successful history of manipulating, processing and extracting value from large disconnected datasets for the purposes of creating datasets that mean functional / non-functional business requirements.
- Experience with data pipeline and workflow management tools such as Azkaban, Luigi, Airflow, etc.
- Experience with at least one of the major cloud services (Google / AWS / Azure) and their associated data technologies (e.g. EMR/RDS/Redshift for AWS), OpenStack experience a strong plus.
- Strong knowledge of at least one major programming language (Python, Java, Scala, etc).
- Ability to work across structured, semi-structured, and unstructured data, extracting information and identifying linkages across disparate data sets
- Experience with data wrangling and feature engineering for machine learning applications.
- Base salary dependent upon experience
- Company share option scheme
- 5% employer matched Pension scheme
- BUPA Health Insurance including Partners and Children cover
- Free Gym Membership
- Cycle to work scheme