Senior Manager Data Engineering

Expect more. Connect more. Be more at Diebold Nixdorf.  Our teams automate, digitize, and transform the way more than 75 million people around the globe bank and shop in this hyper-connected, consumer-centric world. Join us in connecting people to commerce in this vital, rewarding role.

Provides leadership across Data Engineering, data platform architecture, and enterprise data modernization. Designs, develops, and evolves scalable approaches for how data is ingested, stored, transformed, governed, integrated, and consumed across the organization.

Partners with Data Engineering, Analytics, AI, Architecture, Security, and business teams to establish modern engineering standards and data architectures. Brings strong experience with cloud data platforms, including Microsoft Fabric, medallion architecture, semantic layers, ontology, metadata, knowledge graphs, and data governance.

• Provide technical leadership across Data Engineering and data platform architecture.

• Work with business and technology stakeholders to understand objectives and define scalable data architectures.

• Define standards for data ingestion, ETL/ELT, transformation, storage, integration, and consumption.

• Establish modern lakehouse and medallion architecture patterns for enterprise data platforms.

• Partner with Data Engineering teams to improve engineering practices, platform capabilities, reliability, and performance.

• Establish and advance data governance practices across data quality, lineage, metadata, access, retention, and lifecycle management.

• Develop semantic layer, ontology, and knowledge graph capabilities to improve consistency and usability of enterprise data.

• Identify opportunities to apply new technologies and processes that improve scalability, efficiency, and business value.

• Bachelor's Degree or equivalent work experience required.

• 8 to 10 years of experience in Data Engineering, Data Architecture, or Data Platforms, with 2-4 years of leadership experience.

• Strong knowledge of cloud data platforms, lakehouse and medallion architecture, ETL/ELT, data modeling, and data governance.

• Experience with Microsoft Fabric, Azure data services, OneLake, or comparable modern data platforms.

• Understanding of semantic layers, metadata management, ontology, and knowledge graph concepts.

• Fluent written and verbal English communication skills.