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# Information Technology - Data Analyst

- **Company:** Indotronix Avani Group
- **Location:** Alafaya, FL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $208,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Data Infrastructure, JSON, SAP (Applications), SAP S/4HANA
- **Published:** October 5, 2026
- **Apply:** https://candidateportal.ceipal.com/job-details/IeP3lG1nwMtBhhFshof2iMAVc8OhISc1-iHafmgv4sY

## About the Role

Extensive experience (15+ years) in SAP S4/HANA Analytics.

 - Advanced proficiency in HANA XSA data modeling.
 - Deep understanding of data security concepts, particularly row level security.
 - Demonstrated ability to use analytic privileges and roles for data protection.
 - Strong analytical and troubleshooting skills for model performance issues.
 - Proven collaborative skills working with multiple developer groups.

Preferred Skills

 - Familiarity with emerging SAP technologies.
 - Experience in large, enterprise-scale data environments.
 - Knowledge of agile methodologies and cross-functional team operations.

## Description

Join an innovative tech team as a Data Analyst specializing in SAP S4/HANA Analytics. You'll leverage your expertise in HANA XSA data modeling, data security, and performance troubleshooting to drive impactful solutions and support collaborative development. This is an ideal opportunity for a seasoned professional seeking a dynamic environment with strong career growth potential., Develop and modify SAP S4/HANA XSA data models to optimize business analytics.

 - Implement and maintain row level security in data models, ensuring strict data confidentiality.
 - Apply and manage analytic privileges and roles for robust access control.
 - Diagnose and resolve performance and execution issues in data models for high efficiency.
 - Provide expert support and troubleshooting for data in shared repositories and cross-functional teams.
 - Collaborate with and mentor other data modelers, offering constructive feedback and technical guidance.
 - Review and enhance data modeling practices to align with best-in-class standards.