Job Description
* Architect and implement robust ETL pipelines to extract data from SAP ECC, SAP S/4 HANA, SAP HANA, and SAP Datasphere using best-practice integration methods (e.g., ODP, CDS views, RFCs, BAPIs).
* Analyze and interpret SAP’s internal data models (e.g., tables like BKPF, BSEG, MARA, EKPO) and work closely with SAP functional and technical teams.
* Work with SAP Datasphere (SAP Data Warehouse Cloud) to federate or replicate SAP data for consumption in the EDP (highly desired).
* Review or interpret ABAP logic when necessary to understand legacy transformation rules and business logic (nice to have).
* Lead the end-to-end data integration process from SAP ECC, ensuring deep alignment with the EDP’s design and downstream data usage needs.
* Leverage knowledge of HANA Data Warehouse and SAP BW to support historical reporting and semantic modeling.
* Design and build robust, scalable ETL/ELT pipelines to ingest data into Microsoft cloud using tools such as Azure Data Factory, or Alteryx.
* Automate data movement from SAP into Azure Data Lake Storage / OneLake, enabling clean handoffs for consumption by Power BI, data science models, and APIs.
* Build data transformations in SQL, Python, and PySpark, leveraging distributed compute (e.g., Synapse or Spark pools).
* Work closely with cloud architects to ensure integration patterns are secure, cost-effective, and meet performance SLAs.
Note: The original description was somewhat cluttered, and I have cleaned it up for clarity and readability while preserving all essential information.
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