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SAP Datasphere Consultant || Immediate Joiner

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Onsite

SAP Datasphere Consultant || Immediate Joiner

Abhiyanta India Solutions

SAP Datasphere Consultant || Immediate Joiner

Skills

SQL QueriesData MiningData AnalysisSAP ERPSAP Analytics Cloud

2 months ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Onsite

Published on:

24 August 2026

What they need


Job Title: SAP Datasphere

Qualifications & Skills

  • Experience: 2 - 5 years of hands-on experience in SAP data and analytics technologies, with a strong focus on SAP Datasphere
  • Core Competencies: Proficiency in Data Builder, Business Builder, Analytical Models, and BW Bridge.
  • Technical Proficiencies: Advanced SQL scripting and familiarity with CDS views.
  • Ecosystem Knowledge: Strong understanding of source systems including SAP S/4HANA, BW/4HANA, ECC, and SAP Analytics Cloud (SAC).
  • Integration Techniques: Hands-on experience with OData, APIs, replication flows, and Data Provisioning (DP) Agents.
  • Soft Skills: Excellent problem-solving abilities and a proven track record of translating complex business requirements into enterprise-ready data products.

Key Responsibilities

  • Data Modeling & Architecture: Design and build semantic models, Analytical Datasets, and Business Layers utilizing the SAP Datasphere Data Builder and Business Builder.
  • ETL & Data Integration: Develop and optimize Data Flows, Replication Flows, and Transformation rules to extract and harmonize data from diverse SAP and non-SAP sources.
  • SQL & CDS Views: Write and optimize complex SQL queries for data extraction and transformation; configure and manage CDS views for SAP S/4HANA integrations.
  • Cross-Platform Integration: Integrate Datasphere semantics directly with SAP Analytics Cloud (SAC) to support KPI-rich dashboards and analytic applications.
  • Governance & Security: Implement Data Access Controls, Space management, and governance standards to ensure data quality and lineage across the landscape.
  • Performance Optimization: Monitor Data Integration tasks, troubleshoot data pipeline issues, and optimize queries for scalability and accuracy.

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