About the role
IT Data Analytics and AI is a diverse DataOps team of technology enthusiasts enabling our global business. Our team is charged with catalyzing value creation in the most critical areas of Aptiv’s value chain, touching our business by understanding customer demand, manufacturing implications, and our supply base. This is a senior manager–level, hands-on technical leadership role responsible for architecting, delivering, and operating Aptiv’s enterprise analytics and AI capabilities.
The role combines deep technical expertise with people leadership, owning large-scale analytics platforms, advanced data architecture, and enterprise agentic AI enablement using Microsoft Copilot Studio and Microsoft Foundry. Your Role: Work collaboratively with all levels of business and technology stakeholders to architect, implement and test Bigdata-based analytical solutions from disparate sources. Create and oversee best practices around ingestion, transformation, data modelling & visualization to ensure high data quality and reduced redundancy. Establish, maintain, and adhere to Enterprise Data Standards & Policies. Own the enterprise analytics and AI ecosystem, including platforms, tooling, integrations, and cloud services. Develop best practices for standard naming conventions and coding. Lead a team of data architects and analysts and is Responsible for technical design quality, delivery outcomes, platform reliability, and the continuous evolution of the analytics and AI ecosystem. Connect with the functional and technical leads when prioritizing the technology initiatives to support analytics. Work with leadership and stakeholders to define the overall vision, mission, and strategy for business data models that scales up for the enterprise. Mentor & guide technical project teams based globally on Google data platform components. Line management of technical teams to delivery and maintain analytics and AI solutions Continuous improvement, enrichment and governance as part of DataOps operating model. Ensure high engineering standards, solution quality, and technical integrity across all analytics and AI initiatives. Balance innovation with operational stability through a mature DataOps operating model. Establish operational standards for monitoring, performance optimisation, incident management, and cost control. Your Background: Bachelor of Science degree and/or master’s in software engineering / Computer Science or an equivalent discipline. 8 + yrs. of experience using various development methodologies to deliver robust IaaS, SaaS and PaaS-based analytics solutions. Proven expertise on Google Cloud Platform: BigQuery, Dataproc, Dataplex, Looker, Cloud data fusion, Data Catalog, Dataflow, Cloud composer, Analytics Hub, Pub/Sub, Dataprep, Cloud Bigtable, Cloud SQL, Cloud IAM, Google Kubernetes engine, AutoML. Exposure to AWS, Azure, Hadoop platforms. Object Oriented Programing skills using Java, Python, and .Net. ETL/ELT Framework design and implementation. Demonstrated experience with technical troubleshooting, log analysis and performance optimization. Microsoft Copilot Studio – design, configuration, and delivery of enterprise AI agents. Microsoft Foundry – AI lifecycle management, governance, and operationalisation. Azure Data & Analytics services (e.g., Azure Synapse, Microsoft Fabric, Azure Data Factory, Azure SQL). Microsoft Entra ID – identity, access management, and security integration. Understanding of Responsible AI, security, and compliance within Microsoft platforms.
