Manufacturing Process Engineer optimizing production processes at Ingeteam. Collaborating with cross - functional teams to enhance efficiency and standards across various locations in Spain.
About the role
- Principal Data and Asset Management Engineer leading CMDB and asset management solutions at NVIDIA. Focused on data accuracy, automation, and collaboration across teams.
Responsibilities
- Architect and lead the design of enterprise-scale CMDB and asset management systems, defining authoritative data models for infrastructure, software, services, and their relationships across the lifecycle
- Own the data architecture and integration strategy for asset and configuration data, spanning discovery systems, provisioning tools, cloud platforms, monitoring systems, and internal services
- Design, build, and maintain robust ETL/ELT pipelines that ingest, normalize, validate, and reconcile asset data from many heterogeneous sources
- Establish and enforce data quality standards, including validation rules, reconciliation logic, lineage, and auditing to ensure CMDB accuracy and trustworthiness
- Build and evolve highly reliable APIs and data services that enable engineers, IT, and business systems to query and manage asset and configuration data at scale
- Develop automation for asset lifecycle management (onboarding, change, decommissioning), dependency tracking, and impact analysis
- Partner closely with infrastructure, SRE, IT, security, and finance teams to ensure CMDB data supports operational workflows, compliance, capacity planning, and cost attribution
- Provide technical leadership and mentorship, influencing best practices in data engineering, system design, and operational excellence across the organization
- Drive technical roadmap decisions, evaluate technologies, and lead complex initiatives from design through production
Requirements
- Bachelor’s degree or equivalent experience
- 15+ Years of Software engineering experience, with a proven track record of designing and owning complex, long-lived systems
- Deep experience building data-intensive backend systems, including ETL pipelines, data services, and production APIs
- Strong expertise in Python (and/or Go) for data pipelines, automation, and service development
- Hands-on experience with CMDBs, asset inventory systems, or large-scale metadata platforms, including schema design and relationship modeling
- Experience implementing data validation, reconciliation, and monitoring in production environments
- Solid understanding of CI/CD, containerized deployments, Kubernetes, and cloud platforms (e.g., AWS)
- Experience working with relational and/or NoSQL databases and designing scalable data models
- Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Benefits
- eligible for equity
- benefits
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