SAP Datasphere Consultant

• Provide L2/L3 production support for SAP Datasphere, ensuring timely incident resolution, troubleshooting, root cause analysis (RCA), and adherence to SLAs.
  
• Develop, maintain, and support SAP Datasphere data models, spaces, views, and analytical models based on business and reporting requirements
  
• Manage data integration from SAP source systems, particularly SAP S/4HANA, using data flows, replication flows, and task chains.
  
• Monitor scheduled data loads, identify failures, troubleshoot integration issues, and ensure data availability and consistency.
  
• Write and optimize SQL queries and data transformation logic to support efficient data processing and reporting.
  
• Perform source-to-target data reconciliation and validation to identify discrepancies and ensure data accuracy, completeness, and consistency.
  
• Investigate data inconsistencies and performance issues, implement corrective actions, and recommend improvements to data models and data flows.
  
• Support finance-related data and reporting requirements, including General Ledger (GL), Accounts Payable (AP), Accounts Receivable (AR), Cost Center Accounting, and Profitability Analysis.
  
• Validate financial reports and datasets used for trial balance, Profit and Loss (P&L), balance sheet, and month-end closing activities.
  
• Collaborate with functional teams, business users, and technical stakeholders to understand issues, assess business impact, and deliver effective solutions.
  
• Maintain technical documentation, incident logs, RCA reports, and support procedures, ensuring compliance with support processes.
  
• Provide support for SAP Analytics Cloud (SAC) analytical models, stories, and reporting issues, ensuring accurate data consumption and presentation.
  

Requirements

1. SAP Datasphere Expertise: Hands-on experience in SAP Datasphere development, support, data modeling, spaces, views, and analytical models.
   
2. Production Support: Experience in L2/L3 support, incident management, troubleshooting, root cause analysis (RCA), and SLA-based issue resolution.
   
3. Data Integration: Knowledge of data flows, replication flows, task chains, scheduling, and monitoring data loads.
   
4. SQL and Data Modeling: Strong SQL skills, data transformation logic, query optimization, and troubleshooting data inconsistencies.
   
5. SAP Source Systems: Experience integrating with SAP S/4HANA.
   
6. Data Reconciliation: Ability to validate source-to-target data, identify discrepancies, and ensure data accuracy and completeness.
   
7. Finance Functional Knowledge (Preferred): Understanding of SAP FI/CO processes, including General Ledger (GL), Accounts Payable (AP), Accounts Receivable (AR), Cost Center Accounting, and Profitability Analysis.
   
8. Financial Reporting: Knowledge of finance reporting requirements, such as trial balance, P&L, balance sheet, and month-end closing reports.
   
9. SAP Analytics Cloud (Preferred): Exposure to SAC stories, analytical models, reporting, and troubleshooting data-related issues.