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Data Platform lead - SAS
Job in
Raritan, Somerset County, New Jersey, 08869, USA
Listed on 2026-09-20
Listing for:
Shrive Technologies LLC
Full Time
position Listed on 2026-09-20
Job specializations:
-
IT/Tech
Cloud Computing: Infrastructure & Operations, Information Security & Data Protection, Systems Administrator
Job Description & How to Apply Below
Provide expert-level support, maintenance, and troubleshooting for statistical analysis software platforms (e.g., SAS, R, SPSS, Python-based environments).
- Monitor platform performance, ensure high availability, and proactively resolve incidents and technical issues.
- Collaborate with cross-functional teams to implement software updates, patches, and enhancements while minimizing downtime.
- Assist in the integration of statistical analysis tools with enterprise data sources and reporting solutions.
- Develop and execute platform activity reports, usage analytics, and capacity planning documentation.
- Ensure compliance with organizational security policies, license management, and audit requirements.
- Coordinate with vendors and technology partners for issue resolution and service improvement.
- Provide technical guidance and mentorship to junior team members and contribute to knowledge-sharing initiatives.
- 5+ years of experience supporting and administering statistical analysis software platforms in an enterprise environment.
- Proficiency in SAS, R, SPSS, or equivalent statistical software, with a strong understanding of installation, configuration, and maintenance procedures.
- Experience with scripting languages (e.g., Python, Shell, Power Shell) for automation and platform management.
- Solid grasp of Linux/UNIX and Windows operating systems.
- Strong problem-solving, analytical, and troubleshooting skills.
- Excellent communication and documentation abilities.
- Relevant certifications in statistical software platforms or IT infrastructure (e.g., SAS Certified Platform Administrator, ITIL).
- Experience with cloud-based analytics platforms or containerization technologies (e.g., AWS, Azure, Docker).
- Familiarity with data security standards and compliance frameworks.
- Background in supporting large-scale analytics or data science projects.
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