Cloud Data Solutions Consultant
Remote Location, United States
The Ohio State University
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Job Title:
Cloud Data Solutions ConsultantDepartment:
CCC | Information TechnologyJob Summary:
The Cloud Data Solutions Analyst 4 plays a critical role in supporting cancer research through the design, development, and management of both on premises and advanced cloud-based data platforms. Functions as a senior-level cloud engineer and solutions architect, playing a pivotal role in enabling precision oncology and biomedical research through advanced a hybrid on prem and cloud based infrastructure. This role requires an in-depth understanding of distributed systems, hybrid and multi-cloud strategies and practices to support complex, data-intensive scientific workflows. This position serves as a technical leader and strategic partner in building scalable, secure, and high-performing infrastructures to support large-scale research data, AI-driven analytics, and bioinformatics workflows. The role requires deep expertise in Linux and Windows systems, cloud computing, and the ability to collaborate effectively with research scientists and cross-disciplinary teams. The analyst partners with researchers, bioinformaticians, and data scientists to provision elastic, fault-tolerant systems for genomic pipelines, AI/ML model inference, and large-scale data lake analytics, ensuring compliance with rigorous data governance and regulatory frameworks (HIPAA, NIST).
Key Responsibilities:
- Architect and implement secure, scalable, and high-performance on premises and cloud environments (AWS, Azure) to support cancer research applications and data pipelines.
- Support data integration, management, and analysis for large genomic, clinical, and imaging datasets. Including data protection and safeguarding of cancer research data.
- Collaborate with data scientists, bioinformaticians, and AI researchers to operationalize machine learning models and analytics workflows in the cloud and on premises.
- Maintain and troubleshoot Linux and Windows based hybrid of cloud and on premises infrastructure to ensure high availability, performance, and security.
- Lead incident response, root cause analysis (RCA), and continuous improvement cycles for research services.
- Guide adherence to compliance frameworks including HIPAA, NIST, and institutional IRB protocols by implementing encryption-at-rest/in-transit, audit logging, vulnerability scanning, and DLP solutions.
- Monitor all infrastructure systems for compliance and up time.
- Lead the implementation of automation tools (e.g., Globus, Microsoft Orchestrator PowerShell, Bash, Python) to streamline infrastructure deployment and system administration.
- Provide cloud security and compliance guidance in alignment with HIPAA, NIST, and institutional data governance standards.
- Mentor junior staff and contribute to internal knowledge-sharing efforts.
Qualifications:
- Required : Bachelor's degree and a minimum of 6 years in IT infrastructure, cloud computing, or related field.
- Preferred Experience: 12+ years of experience in architecture and solutions development, especially in life sciences or academic research settings.
Domain-Specific Knowledge:
- Experience working with cancer research data, bioinformatics pipelines.
- Familiarity with research computing environments, high-performance computing (HPC), and data lakes used in medical or life sciences settings.
- Understanding of regulatory compliance requirements specific to biomedical research, including IRB, HIPAA, and NIH Genomic Data Sharing policies.
Technical Skills and Competencies:
- Cloud Platforms: Deep expertise in AWS, Azure, etc.
- Operating Systems:
- Expert knowledge of Linux administration skills (e.g., RHEL, AlmaLinux, Ubuntu). Python and Bash scripting. Including configuration management and endpoint architecture.
- Expert knowledge with Windows Server environments, including Active Directory and PowerShell scripting. Including configuration management and endpoint architecture (SCCM, Orchestrator etc.).
- AI & Data Science Support:
- Experience integrating AI/ML pipelines into production environments.
- Familiarity with tools in cloud settings.
- DevOps & Automation:
- Expertise with GitOps workflows, container orchestration (Docker, Kubernetes, Podman), service and secrets management (PAM, AWS KMS).
- Proficiency in containerization (Docker, Kubernetes, Podman). API code writing for integration into other systems
- Automation with IAC (Infrastructure As Code) including GitOps and Ansible
- Security & Compliance: Knowledge of security best practices for research data, including HIPAA, NIST, and institutional standards. Including mitigation and analysis. Federated identity management, vulnerability scanning (Tenable). Experience supporting security audits and generating system accreditation artifacts for IRB.
- Soft Skills: Excellent problem-solving, project management, and communication skills with the ability to work in a collaborative, research-driven environment. Proven ability to work across interdisciplinary teams, translate research needs into technical solutions, and communicate complex concepts clearly to both technical and non-technical stakeholders.
Function: Information Technology
Sub Function: Cloud Data Solutions
Career Band: Individual Contributor - Specialized
Career Level: S4
Additional Information:
Location:
Remote LocationPosition Type:
RegularScheduled Hours:
40Shift:
First ShiftFinal candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.
Thank you for your interest in positions at The Ohio State University and Wexner Medical Center. Once you have applied, the most updated information on the status of your application can be found by visiting the Candidate Home section of this site. Please view your submitted applications by logging in and reviewing your status. For answers to additional questions please review the frequently asked questions.
The university is an equal opportunity employer, including veterans and disability.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Ansible APIs Architecture AWS Azure Bioinformatics Data governance Data pipelines DevOps Distributed Systems Docker HPC Kubernetes Linux Machine Learning ML models Model inference Pipelines Python Research Security
Perks/benefits: Career development
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