Job Description
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
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
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