SAP Data Architect

• Fully remote
• Project overview and estimated length: Project goal it to integrated a Snowflake-based data platform with SAP HANA-based source systems, including SAP CFIN (S/4HANA), BW/4HANA, and MDG.
• Duration: 6 months extension possible
• Recruitment stages: 2 meetings: one with technical person (current architect in the rol), second meeting with Project Manager.
• Client: This Swiss-based global company specializes in electrification, automation, and robotics.

Our requirements

• Proven experience as an SAP Analytics Architect with a strong understanding of SAP HANA and SAP ecosystem.
•  Deep knowledge of SAP source systems, including S/4HANA, CFIN, BW/4HANA, and MDG.
• Expertise in data integration methodologies, tools, and best practices.
• Strong analytical and problem-solving skills with the ability to address complex technical challenges.
•  Excellent communication and collaboration skills to effectively work with crossfunctional teams
• Very good command of English and Polish - to the extent that you can understand and create technical documentation, create presentations and work in an international team.

Your responsibilities

• SAP Data & Analytics Architect to play a key role in a customer project. The person will be responsible for integrating a Snowflake-based data platform with SAP HANA-based source systems, including SAP CFIN (S/4HANA), BW/4HANA, and MDG.

Key Responsibilities:

• Define and design the architecture for ingesting data from SAP HANA based transactional systems into the Snowflake data platform.
• Develop an integration strategy:

1.  Tool Selection: evaluate and select appropriate tools and technologies for data ingestion and transformation.
2. Proof of Concept (POC): lead and execute Proof of Concept initiatives to validate the chosen integration approach and technologies.

•  Incorporate and address non-functional requirements such as security, performance, and data quality throughout the integration process.
• Understand and assess the impact of SAP licensing models on data extraction strategies. Evaluate and recommend the most suitable data extraction methods, including database level extraction, ABAP layer extraction, ODP (Open Data Protocol) layer extraction.
• Support the building of data models, for example based on ACDOCA, with efficient delta extraction mechanisms