LEAD DATA ENGINEERING, INTEGRATION & GOVERNANCE
bOverview /b pIn this role, you will architect and operate the data engineering foundation for the Digital Engineering Data Strategy, enabling trusted, interoperable data across enterprise systems. You collaborate with cross-functional teams to support semantic platforms, Digital Twins, AAS, and analytics, ensuring data quality and traceability. You will drive scalable data pipelines, integration patterns, and governance to empower a data-driven Digital Engineering organization. This position offers impact through enabling enterprise interoperability and sustainable data products. You will work hybrid from Bangalore within ABB Smart Power, contributing to energy-efficient and data-enabled solutions. /p bResponsabilità /bulliDesign and evolve scalable data architectures and integration patterns for enterprise ingestion and interoperability. /liliBuild and operate ETL/ELT pipelines, APIs, and reusable data products for downstream consumption and semantic platforms. /liliLead data preparation, transformation, enrichment, and semantic mapping for knowledge graphs and catalog publication. /liliEstablish data quality, lineage, monitoring, and version-control across platforms. /liliOversee pipeline operations, governance, security, and lifecycle controls with policy embedding and catalog integration. /liliOptimize data platforms infrastructure,
performance, availability, and disaster recovery. /liliPrepare and expose semantically ready data for ontologies, knowledge graphs, and semantic layers. /liliCollaborate with stakeholders to scale Digital Engineering CoE standards and best practices. /li /ul bRequisiti fondamentali /bulliLarge-scale data experience in complex enterprise environments /liliProven track record designing data pipelines and reusable data products /liliExperience with data quality, metadata management, lifecycle and governance /liliHands-on ETL/ELT, data ingestion, transformation, and quality automation /liliPractical experience with Databricks, Azure Data Factory or similar /liliKnowledge of metadata management, data catalogs/registries, lineage and traceability /liliExposure to semantic integration, knowledge graphs, ontology-driven architectures a plus /liliExcellent communication with business stakeholders /liliStrong problem-solving and ownership mindset /liliAbility to influence across organizational structures without direct authority /li /ulullistrong communication /lilicross-functional collaboration /liliownership and initiative /lilidata engineering /liliETL/ELT pipelines /lilidata ingestion and transformation /li /ul
performance, availability, and disaster recovery. /liliPrepare and expose semantically ready data for ontologies, knowledge graphs, and semantic layers. /liliCollaborate with stakeholders to scale Digital Engineering CoE standards and best practices. /li /ul bRequisiti fondamentali /bulliLarge-scale data experience in complex enterprise environments /liliProven track record designing data pipelines and reusable data products /liliExperience with data quality, metadata management, lifecycle and governance /liliHands-on ETL/ELT, data ingestion, transformation, and quality automation /liliPractical experience with Databricks, Azure Data Factory or similar /liliKnowledge of metadata management, data catalogs/registries, lineage and traceability /liliExposure to semantic integration, knowledge graphs, ontology-driven architectures a plus /liliExcellent communication with business stakeholders /liliStrong problem-solving and ownership mindset /liliAbility to influence across organizational structures without direct authority /li /ulullistrong communication /lilicross-functional collaboration /liliownership and initiative /lilidata engineering /liliETL/ELT pipelines /lilidata ingestion and transformation /li /ul