SAP Data Engineer: Build Modern Data Products

Miele; Poznań; On-site; PLN 180,000 - 240,000; Full time

Job summary

Miele is seeking a skilled SAP Data Engineer in Poznań to design, build and operate data products using SAP Datasphere and SAP Business Data Cloud. The role emphasizes evaluating extraction approaches, handling delta processes, and ensuring data quality within a growing SAP-centric data landscape.

You will modernize BW/BW4 data models, collaborate with data architects, consultants, and IT teams, and contribute to a scalable data architecture suited for enterprise analytics.

Qualifications

• Experience in data engineering, data warehousing or analytical data modeling in the SAP environment.
• Good understanding of SAP source systems and data structures, preferably S/4HANA.
• Strong ABAP and SQL and data modeling skills.
• Knowledge of Python, ABAP OO, SQLScript and CDS is desirable, plus basic data security and GDPR awareness.

Responsibilities

• Design, build and operate reusable data products using SAP Datasphere and SAP Business Data Cloud based on business processes that can be integrated in open source data platforms.
• Evaluate SAP extraction and integration approaches, considering delta handling, data volumes, performance, data quality and operational impact.
• Modernize the existing SAP BW and BW4 data models and flows by designing future architecture.
• Work closely with data architects, external consultants, business experts, IT teams.

Skills

Data engineering

Data warehousing

Analytical data modeling

SAP data concepts

Communication

Tools

SAP Datasphere

SAP BW/4HANA

SAP Business Data Cloud

SQL

ABAP

CDS

Python

Job description

Miele is seeking a skilled SAP Data Engineer in Poznań to design, build and operate data products using SAP Datasphere and SAP Business Data Cloud. The role emphasizes evaluating extraction approaches, handling delta processes, and ensuring data quality within a growing SAP-centric data landscape.

You will modernize BW/BW4 data models, collaborate with data architects, consultants, and IT teams, and contribute to a scalable data architecture suited for enterprise analytics.