Understanding the business use of data and the stakeholders’ requirements to support work processes– specifically on data conversion, and strategic business objectives.
Leverage data and software engineering techniques, data science to create business value through data accessibility (includes data ingestion, data preparation, analytical processing and data conversion).
Identifying, acquiring, cleansing/preparing, storing data and developing reusable data products aligned with defined architecture patterns.
Enabling data scientists, making data available for advanced analytics models, and contributing to advanced analytics models.
Develop jobs for ingestion of SAP and/or other ERP data (e.g. DE) into the lake.
Develop jobs for ingestion of lake data into S/4HANA.
Contribute in operationalizing SAP and/or other ERP system data into the lake.
Develop ECC CDS views that will be the data source of the data ingestion of SAP and/or other ERP system data.
Explore Azure Synapse tool on how this can be used and develop solutions on data validation of SAP and/or JDE in the lake.
Working with data analysts and architects to scale and deploy solutions including models, documentation, training, integration.
Contributing to the inner source development of foundational tools, and/or the deployment of technical services.

BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.
At least 3 years of ETL experience and has performed development work on SAP Data Services (BODS) as part of SAP data conversion.
Knowledge in the Oil & Gas industry ERP, SAP and/or JDE Functional experience or domain knowledge.
Knowledge and/or experience with: data acquisition, preparation and validation; data conversion from extract, transform and load, data movement and transformation; analytics solution architecture; big data computing; cloud computing, core data architecture; information security technologies and software engineering using technologies such as: SAP Data Services(BODS),SAP Landscape Transformation Replication Server (SLT), Azure Data Factory (ETL),Azure Data Lake, DevOps, CI/CD Pipeline Deployment, Python, T
SQL, Azure SQL, Azure Synapse, GIT, ADO.
Proven years of experiences to adopt software engineering practices in managing data products.
Analytical thinking, consulting, critical thinking.

SAP Data Engineer

Key skills