Data Science Dev/Ops Engineer

To be part of our organization, every employee should understand and share in the YNHHS Vision, support our Mission, and live our Values. These values - integrity, patient-centered, respect, accountability, and compassion - must guide what we do, as individuals and professionals, every day.

ITS Lead Data Science Dev/Ops Engineer will be an experienced system administrator and DevOps engineer with aproven track record of managing distributed hardware and software environments, integrating emerging technologies and working within a collaborative development and analytics environment. The individual will be responsible for management of dedicated and virtual environments that run data science platforms using Kubernettes. The individual must have familiarity with both Linux and Windows environments.

EEO/AA/Disability/Veteran

1. System Management /DevOps

1.1 Coordinates and supports Ubuntu Linux engineering and operations

1.2 Deploying, managing and administering Kubernetes

1.3 Manages container workloads (Kubernetes)

1.4 Develops and supports Infrastructure as code (Python, Ansible, Helm, GitLab)

1.5 Monitoring and alerting (Prometheus)

1.6 Coordinates and supports Nutanix operations (management of virtual servers)

1.7 Researches new technologies or methods to advance technical capabilities of the Co-op Works with system owners to consult on system design and gather technical requirements fo rcomplex IT systems

1.8 Experience designing to high availability and disaster recovery requirements. This includes designing system across data centers, clusters and within data centers including failover testing

1.9 Ability to draft system documentation inclusive of KB articles, technical specifications, architecture diagrams

1.10 Knowledge of storage systems (NAS, SAN, AWS S3)

2. Data Management

2.1 Participates in the creation of data management plans for key projects

2.2 Develops data inventory for new data sets within the platform

3. Application Development

3.1 Assists with defining application use cases and requirements

3.2 Assists with the development and review of enterprise application architectures

3.3 Consults with team members related to healthcare database access, particularly for Epic-related data warehouse systems

3.4 Builds new tools to automate workflows

3.5 Ability to develop applications within a data science platform

4. Teamwork

4.1 Creates and maintains regular status reports

4.2 Attends weekly team meetings to discuss team and project related activities, issues, change, communications, and updates

4.3 Completes specific task activities as documented in work plans

4.4 Supports department with application and information systems knowledge

4.5 Promotes a team atmosphere that is conducive to the overall accomplishment of goals, schedules, and deadlines

4.6 Openly shares information with all team members

5. Documentation

5.1 Documents and maintains all required architecture and software comments and configures systems accordingly

5.2 Contributes to preparation of testing scripts and materials and performs unit, system, and integrated testing tasks

5.3 Assists with implementation and deployment plans and contributes information to change control process

5.4 Provides expertise and experience to the development of production environment readiness plan

6. Other

6.1 Provides training to other staff as appropriate

6.2 Helps coordinate interactions with vendors

6.3 Work closely with departmental staff to identify needs and benefits of implementing software solutions and strives to understand their needs

EDUCATION

Bachelor's Degree required, Master's Degree in Healthcare Administration, ITS, or related field preferred.

EXPERIENCE

Three to four years of experience in healthcare information technology. Seven to ten years prior experience in ITS, electronic health records or data science platforms. Prior experience in Healthcare or other regulated environment (such as financial services) preferred.

SPECIAL SKILLS

Strong background in Linux and Windows system administration. Experience with deployment and maintenance of the Kubernetes platform. Knowledge of Python and other data science tools. Familiarity with Kerberos and or Active Directory configuration. Knowledge of DevOps tools (Ansible) for deployment and configuration of infrastructure, container orchestration and implementation of security frameworks within a distributed environment for application deployments.