SAP Data Engineer

SAP Data Engineer — (FinTech)

Role Summary

Data Warehouse & Analytics Developer to design, build and maintain scalable data models and analytics solutions on SAP Datasphere, Snowflake, dbt, SAP Analytics Cloud (SAC) and Tableau — supporting a greenfield SAP S/4HANA RISE implementation and the modernization of the broader data landscape.

Key Responsibilities

• Translate business requirements and logical data models into optimized physical data models in SAP Datasphere and Snowflake.
• Maintain CDS Views in SAP S/4HANA for real-time data extraction; build data models, views, table functions and replication tasks in Datasphere/Business Data Cloud.
• Develop, optimize and maintain dbt models, macros and orchestration workflows, using Docker Desktop containers in VS Code for isolated, consistent dev environments.
• Write high-performance SQL, stored procedures and tasks in Snowflake to support analytical layers.
• Design and optimize dashboards, stories and analytical apps in SAC and Tableau (live and acquired connections).
• Own technical design documentation, test cases, unit/integration testing, and support UAT.
• Support production deployments, troubleshoot data pipelines, and provide hypercare/post-go-live support.
• Follow CI/CD, SDLC and enterprise naming/performance standards.
• Use AI-assisted tools (e.g. Claude, Gemini) to accelerate development, documentation and debugging.

Required Skills

• SAP HANA 2.0 XSA — data flows, DWF, complex SQLScript (must)
• SDLC, CI/CD, Git/version control, logical & physical data modeling (must)
• Advanced SQL

Strong Advantage

• SAP Datasphere (Business Data Cloud), SAC, S/4HANA, ABAP CDS Views

Nice to Have

• dbt (Core/Cloud), Docker Desktop, VS Code
• Snowflake (Virtual Warehouses, Snowsight), Tableau