LEAD DATA ENGINEERING, INTEGRATION
Pubblicato il 17-08-2026 - BlackBerry in Bergamo
At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.This Position reports to:Center of Excellence Lead Digital EngineeringYour role and responsibilities :The Lead Data Engineering, Integration & Governance is responsible for building and operating the data engineering foundation for the Digital Engineering Data Strategy. This role leads the ingestion, preparation, transformation, quality assurance, and integration of data from enterprise source systems (PLM, ERP, MES, engineering tools, simulation platforms, product configuration systems). The role ensures data is technically available, trusted, traceable, and ready for consumption by semantic integration layers, knowledge graphs, metadata/catalog capabilities, Digital Twin platforms, Asset Administration Shell (AAS), sustainability platforms, analytics applications, and downstream systems. This role bridges hands-on data engineering, enterprise integration,
operational excellence, and governance implementation to enable a scalable, data-driven Digital Engineering organization.The work model for the role is: #LI- HybridThis role is contributing to the Electrification Business Smart Power Division in Bangalore, IndiaYou will be mainly accountable for:Data Engineering & IntegrationDesign and evolve scalable data engineering architectures, integration patterns, and database structures that enable ingestion and interoperability across enterprise systems.Build and operate robust data integration capabilities, including ETL/ELT pipelines, workflows, APIs, automation frameworks, and reusable data products that support semantic platforms, Digital Twins, AAS, analytics, and other downstream consumers.Data Preparation, Transformation & QualityLead the preparation, transformation, harmonization, enrichment, and semantic mapping of enterprise data for knowled