Our Client is looking for a Senior Datasphere Developer, ERP Reporting & Analytics
Start: January 5, 2025 End Date: 1 Year Contract. Strong chance of a renewal of 6 months Location: Vancouver, BC; Hybrid. 4 days in office, 1 day work from home. Work Type: Contract
Role Overview
The Senior Datasphere Developer, ERP Reporting & Analytics plays a meaningful role in crafting, developing, and optimizing enterprise-wide data models, pipelines, and integrations within SAP Datasphere. This role requires deep knowledge of SAP’s data architecture, strong hands-on development skills, and a solid grasp of SAP BDC.
Working primarily within SAP Datasphere and SAP Analytics Cloud (SAC), the developer will translate reporting and analytical requirements into scalable data solutions, build and enhance analytical and semantic models, ensure reliable data flows, and enable advanced reporting and self-service analytics. This position will work closely with functional teams, business analysts, data architects, and business collaborators to deliver governed, high-performance, and robust ERP reporting solutions that support strategic decision-making and empower self-serve capabilities.
This is an initial 12-month contract to start with strong possibility of extension based on program needs.
The position contributes directly to the success of the ERP transformation program and is measured through:
• Scope of data analysis models and reporting supported: Multi-functional (e.g., Finance, Supply Chain, EAM, Marketing and Logistics)
• Work Products: Number and quality of quantitative models and documentation
• Project Involvement: Participates in ERP implementation projects and ongoing reporting improvements
• Partner Engagement: Collaborates with business analysts, functional teams, data architect, other developers, and data governance leads
• Success Metrics: User adoption rate, report accuracy, ensuring timely delivery of analytical models and reports, rework rate
• Scope includes working across multiple functions (financial operations, supply chain management, asset management, marketing & logistics).
Responsibilities
Build, develop and maintain analytical models, fact and dimension tables in SAP Datasphere
Build and manage end-to-end data pipelines including ingestion, transformation and cleansing and orchestration across SAP and non-SAP systems
Ensure alignment to data governance, data quality, metadata management, and security standards within Datasphere
Collaborate alongside business analysts to understand reporting requirements
Perform unit and integration testing; support user acceptance testing (UAT) where required.
Develop and uphold technical specifications and other required documentation
Ensure compliance with data governance and data quality standards
Provide mentorship and guidance to junior and intermediate data developers as needed.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related field
5+ years of experience in SAP data warehousing including BW, data engineering, or analytics; 2+ years hands-on with SAP Datasphere
Hands on expertise in SAP Datasphere modeling layers, including:
Data Builder (relational datasets, views, data and transformation flows)
Expertise in integrating Datasphere with SAP S/4HANA, SAC, SAP Ariba, SuccessFactors, and external DBs via SDI/SDQ, OData, JDBC/ODBC, DP Agent, and remote tables
Strong SQL skills and experience writing, optimizing, and debugging SQL within Datasphere and HANA Cloud
In-depth knowledge of the Datasphere Space concept, including space isolation, sharing, access control, lifecycle management, and cross-space data sharing
Experience crafting Analytic Models, including measures, associations, hierarchies, and semantic enrichment for advanced analytics
Demonstrable ability to connect and expose Datasphere models to SAP Analytics Cloud (SAC) or BI tools using analytical datasets or OData
Solid grasp of Datasphere governance features, such as data lineage, metadata management, cataloging, and security roles
Good interpersonal skills and ability to lead data architecture discussions in multi-functional teams
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