Azure Cloud Operations Engineer

Azure Cloud Operations Engineer

We are looking for an Azure Cloud Operations Engineer. This is a 6-12+ month contract/contract to hire opportunity with UHG.

Interview process: IKM Test

Remote position

6-12 month contract/contract to hire.

Must have experience with:

• Create and deploy the terraform modules required to build out the infrastructure stack (Azure Big Data ecosystem, i.e. Blob storage / ADLS2, Azure Data Factory, Azure Databricks)
• Create and deploy all the “operations” related aspects of Azure accounts (Security, user authentication, CI/CD framework, logging, monitoring)
• Create and deploy all integration required to acquire from client sources (Azure Data Factory, API, SQL/Oracle/etc.)
• Create and deploy ETL code required to move data through various enrichment layers from staging -> data marts -> data warehouse (Spark, PL/SQL, MSSQL, Python)

Description:

Optum Insight is working to create a plug & play analytics software for their customers, Enterprise Intelligence Platform. This software would be push-button development for clients. Usually this type of service is sold as a SaaS. Their customers are Providers who want to evaluate data regarding facility engagement, facility encounters, duration of stay, etc. Apex will provide a combined onshore and nearshore Scrum Development team to assist in building the Optum Enterprise Intelligence Platform (EIP) that can be used to build insights into Optum’s customers’ strategic workflows and needs.

The platform will be customizable for various Optum’s customers and extensible to add features around data acquisition, data transformation, data validation and insight generation. Optum must produce a Minimum Viable Product (MVP) by October to deliver “first insights” with EIP. The contract with Apex is through October, but will almost certainly go longer. Optum would like to hire consultants who are open to converting to FTE and staying on the team long term.

Tech details… AKA how will they do this?

• Create and deploy the terraform modules required to build out the infrastructure stack (Azure Big Data ecosystem, i.e. Blob storage / ADLS2, Azure Data Factory, Azure Databricks)
• Create and deploy all the “operations” related aspects of Azure accounts (Security, user authentication, CI/CD framework, logging, monitoring)
• Create and deploy all integration required to acquire from client sources (Azure Data Factory, API, SQL/Oracle/etc.)
• Create and deploy ETL code required to move data through various enrichment layers from staging -> data marts -> data warehouse (Spark, PL/SQL, MSSQL, Python)

Timeline for the project:

• Following onboarding and formal project kick-off, the first two weeks will consist of a Sprint 0 to acclimate, provision access, review all workflow processes and communication requirements, identify priorities, and prepare for first Sprint cycle.
• The team will focus on the following objectives and activities during Sprint 0:
• Review current state, ask questions, build understanding and accept as input to User Stories
• Conduct detailed technical review
• Review and prioritize User Stories
• Prepare Test approach
• Review and understand the Agile Delivery Framework provided by UHS (Scrum at Scale and LeSS)
• Two-week Sprints will follow Sprint 0. The project team will participate in Sprint level activities including Backlog Grooming, Sprint Planning, Story Grooming, Test Plan Development, Coding, Testing, Regression Testing, End of Sprint Showcases, Sprint Reports, Sprint Retrospectives, and Conduct Demos.
• Vendor anticipates the MDC nearshore data engineering team will start with Sprint-5

Required Skills:

• Create and deploy the terraform modules required to build out the infrastructure stack (Azure Big Data ecosystem, i.e. Blob storage / ADLS2, Azure Data Factory, Azure Databricks)
• Create and deploy all the "operations" related aspects of Azure accounts (Security, user authentication, CI/CD framework, logging, monitoring)
• Create and deploy all integration required to acquire from client sources (Azure Data Factory, API, SQL/Oracle/etc.)