LEAD DATA ENGINEERING, INTEGRATION & GOVERNANCE

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Questa Posizione Risponde a

Center of Excellence Lead Digital Engineering

Your 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: Hybrid

This role is contributing to the Electrification Business Smart Power Division in Bangalore, India

You Will Be Mainly Accountable For

Data Engineering & Integration

• Design 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 & Quality

• Lead the preparation, transformation, harmonization, enrichment, and semantic mapping of enterprise data for knowledge graph population, registry/catalog publication, and downstream consumption. Establish data quality, validation, traceability, lineage, monitoring, exception-handling, and version-control practices to ensure data accuracy, consistency, usability, and controlled evolution across platforms.

Operations, Governance, Compliance & Lifecycle Management

• Drive operational excellence for data platforms by managing pipeline operations, integration workflows, quality reporting, issue resolution, migration activities, platform upgrades, and continuous improvement initiatives.
• Implement governance, compliance, security, and lifecycle controls by embedding policies, metadata management, catalog integration, access management, auditing, and regulatory requirements into data products and workflows.

Technical Oversight & Infrastructure

• Optimize and maintain enterprise data platforms through infrastructure consolidation, performance tuning, availability and disaster recovery planning, workspace management, automation, monitoring, root-cause analysis, and technology evaluation.

Semantic Enablement & Downstream Consumption

• Prepare and expose semantically ready data that supports ontologies, knowledge graphs, semantic integration layers, and canonical information structures required for enterprise interoperability.
• Enable and support delivery of structured outputs, transformations, and integration mechanisms for Digital Twin platforms, Asset Administration Shell (AAS), Omniverse, sustainability solutions, analytics applications, and other consumer-specific services.

Collaboration & Stakeholder Engagement

• Partner with business stakeholders, architects, semantic modelers, domain experts, vendors, and platform teams to implement end-to-end data integration, maintain technical documentation, and drive scaling of Digital Engineering CoE standards and best practices.

Qualifications For The Role

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems, or related field
• Proven experience working with large-scale data in complex enterprise environments
• Strong track record designing and implementing data pipelines, ingestion frameworks, transformation logic, and reusable data products across multiple enterprise systems
• Experience supporting data quality, metadata management, lifecycle management, operational processes, and technical governance implementation
• Strong hands-on experience with data engineering, ETL/ELT pipelines, data ingestion, transformation, preparation, and quality automation
• Practical experience with modern data engineering platforms and pipeline frameworks (Databricks, Azure Data Factory, or similar orchestration and transformation tools)
• Experience with metadata management, data catalogs/registries, data lineage, and traceability. Exposure to semantic integration, knowledge graphs, and ontology-driven architectures is a plus
• Excellent communication skills—able to bridge the gap between technical teams and business stakeholders
• Strong problem-solving and decision-making abilities, with a hands-on and ownership-driven approach
• Ability to navigate complex organizational structures and influence without direct authority

More About Us

ABB Smart Power provides energy distribution solutions for data centers, industrial and manufacturing plants, critical infrastructure and commercial buildings. The Division’s technical teams work closely with industry partners, delivering advanced solutions that support rapid growth, energy transition, and sustainability objectives. The Division’s portfolio includes industrial circuit breakers, low-voltage systems, motor starting applications, and safety devices like switches and relays. Its Power Protection unit supports the world’s largest data center companies with advanced energy-efficient UPS solutions. The Division’s ABB Ability™ Energy Manager provides a scalable, easy-to-use platform that helps organizations save energy and reduce CO2 emissions.

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