United States Remote

Full-time · Mid-Senior level
201-500 employees · IT Services and IT Consulting

What Success Looks Like:

In 3 months
Learn the different areas of the data connector life cycle, while having a working knowledge of the technical stacks , storage platforms , data models , and Dev. Cycle

- Work within Data Engineering Scrum team

- Set to work on new ingestion pipelines with full bandwidth available (as formal training will end)

In 6 months:
Properly contribute to scrum ceremonies and ceremonies within the dev cycles while successfully updating status and progress in Jira

- Work on higher level enhancement requests and ingestion pipelines

- Ability to Deliver Data related Reviews to clients and other departments regarding code quality and test cases.

- Set your own personal vision of development and career aspirations and set a working path forward with leadership to work on how we can help you attain those goals

In 12 months
Developing a range of data pipelines with varying complexity

- Work with Product, Engineering or Implementation to build out tools for better data integration

- Pick an SME (Subject Matter Expert) path for what excites you the most

- Working on standardized data connector development

What You'll Be Doing:

Design and documentation of connectors / ingestion pipelines
Build and Unit testing of delivery connectors / ingestion pipelines
Support of our processes in partaking in peer code reviews , sprint planning , product grooming , maintaining Jira tasks and peer test reviews
You will be expected to contribute to multiple implementations simultaneously, which will include both new customer setup as well as support and enhancements for existing customers.
The expectations of the day to day of an engineer is as follows:

TECH:

As a data engineer you will be expected to problem solve some basic coding issues and enhancements with frameworks that are built in Spark Scala, while also leveraging technical skills to partake in idea sessions on process improvement and POC design of how to carry out a solution.
SQL: 2-4 year (Preferred)
Spark: 1-2 years (Preferred)
NoSQL Databases: 1-2 years (Preferred)
Database Architecture: 2-3 years (Preferred)
Cloud Architecture: 1-2 years (Preferred)

DATA:

As a data engineer you will be expected to problem solve some basic data analysis issues and work the data to create analytic enhancements.
Healthcare Data: 2-4 years (Preferred)
Healthcare Analytics: 1-3 years (Preferred)