SAP Datasphere Platform Engineer (m/f/d)

About the role

We are looking for a SAP Datasphere Platform Engineer to design, implement and operate the SAP Business Data Cloud platform at BASF’s Digital Hub in Hyderabad. The role bridges architecture, engineering and enablement to ensure reliable technical operations and broad business adoption across data domains.

Key responsibilities

• Design, implement and maintain the SAP Datasphere platform architecture.
• Establish data‑domain‑driven and data‑product‑based design principles.
• Integrate SAP (S/4HANA, BW/4HANA) and non‑SAP sources (Azure, APIs) using ODP, SDI or native connectors.
• Build and optimise data pipelines, semantic models and analytical datasets.
• Ensure robust data governance, access control and security configurations.
• Lead the evolution towards a federated business data fabric model.
• Collaborate with enterprise architects, product family architects, data‑governance and cloud‑infrastructure teams.
• Develop enablement strategies, best‑practice guides and onboarding frameworks for data‑domain teams.
• Conduct training, create documentation and foster a community of practice for self‑service use cases.
• Monitor platform performance, manage incidents and drive continuous improvement through automation (CI/CD, DevOps for data) and usage analytics.

Required profile

• 5+ years of professional experience in data architecture, integration or analytics platforms.
• Proven expertise in SAP Datasphere (formerly SAP Data Warehouse Cloud) administration, modelling and operations.
• Strong knowledge of SAP BTP services, connectivity and hybrid integration technologies.
• Deep understanding of semantic modelling, data pipelines and analytical dataset creation.
• Experience with SAP S/4HANA, SAP BW/4HANA and cloud environments such as Azure.

Required skills

• SAP Datasphere / SAP Data Warehouse Cloud
• SAP Business Technology Platform (BTP)
• SAP S/4HANA and SAP BW/4HANA
• Azure cloud services
• APIs, ODP, SDI connectors
• Data pipeline development
• Semantic modelling
• Data governance and security configuration
• CI/CD and DevOps for data