WOW Softech
SAP DATA Sphere/ SAC Analytics
Skills
1 month ago
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Important information
Contract type:
Permanent
Salary:
₹1,500,000 – ₹1,800,000 / year
Location:
Mumbai, Maharashtra, India
Work mode:
Onsite
Published on:
14 September 2026
What they need
Immediate hiring(Mumbai only). Contact:Preetha. -7200123381
SAP DATA SPHERE/ SAC ANALYTICS
Location: Gurgaon & Mumbai
SCON 5.5. years to 8 years
We are looking for a skilled SAP Datasphere Developer with hands-on experience in data modeling, transformation and ETL within SAP Datasphere. The candidate should have good understanding of CDS views, replication flows, and integration with SAP and non-SAP systems.
Key Responsibilities -
- Design and implement semantic data models in SAP Datasphere using business layer and analytical models.
- Develop data pipelines for ingestion, transformation, and harmonization of data from multiple sources.
- Configure Data Builder for creating tables, views, and transformations.
- Create and optimize CDS views for data extraction from SAP S/4HANA or ECC systems.
- Set up and manage Replication Flows for real-time and batch data synchronization.
- Set up tasks chains for automation of jobs
- Set up Data Access Control for data level authorizations.
- Build SQL based views
- Work with Data Integration Monitor to troubleshoot and optimize replication performance.
- Implement assessment of SAP roadmap and impact on Datasphere
- Ensure compliance with data governance, security policies and performance best practices.
- Collaborate with functional and analytics teams to deliver end-to-end data solutions.
Technical Skills Required: -
SAP Datasphere Core Components:
- Data Builder (Tables, Views, Transformations)
- Business Builder (Business Entities, Semantic Models)
- Data Integration (Replication Flows, Remote Tables, Data Flows)
- SQL based Views
SAP Integration:
- CDS Views for extraction
- ODATA Connections
- Understanding of APIs for data extraction
Nice-to-Have
- Experience with SAP Business Technology Platform (BTP) services.
- Knowledge of data governance and security best practices.
- Exposure to API-based integrations and data virtualization.
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