About rMark Bio
rMark Bio helps life science companies solve for the complexities that come with digital transformation by developing end-to-end AI solutions that deliver personalized business intelligence through integrated applications and API accessible services. Healthcare innovation is best served when individuals with diverse backgrounds come together with a common purpose and clear objectives to improve patient lives. We are product strategists, engineers, data scientists and designers who are experts in our domain and passionate about our mission to accelerate innovation, collaboration and scientific discovery for life sciences
About the role
rMark Bio, is searching for an experienced Data Engineer. Collecting, cleaning, and maintaining large datasets is critical to our business model, so we are building databases of both client and public data in SQL, JSON, Blob, or other types of storage in a Microsoft Azure cloud environment. This data not only supports front end applications, but also critical machine learning software, so good judgment regarding data cleaning and organization is as necessary as strong software skills.Our data engineering is code-centric over cloud platform UIs, but must be efficiently deployable as well. The preferred language for data ETL in Azure is C#, but our data science program is written in Python, so that language may be encountered as well. Building and deploying APIs to access datasets will also be necessary.
- Write robust and deployable software to build and maintain datasets in a Microsoft Azure cloud computing environment.
- Build robust software in Python or C#, as needed
- XML parsing
- Build, organize, and maintain any of SQL, JSON, Blob, or other databases as needed. Experience with graph databases such as Neo4j or Azure Cosmos graph is a plus.
- Write and maintain excellent documentation of all work.
Experience and Qualifications
- Minimum 3-5 years of experience is required
- B.S. in Computer Science or closely related field.
- Programming Languages: C# and Python
- Established expertise in Microsoft Azure Architecture
- Docker – All development is required to be done in a Docker container to maintain a consistent development environment.
- Build and deploy APIs to datasets in Azure
- Data organization, normalization, and cleaning.
- Ability to identify and recommend solutions for problems pertaining to dirty data.
- Work closely with a data science team.
- Databases: SQL, JSON, Blob, etc. Experience with graph databases like Neo4j is a plus.
- Strong technical writing skills will be heavily stressed
Interested? Click here to apply now.