Data Architect, Google Cloud
Summary
Data Architect at Google Cloud serving as the primary technical contact for a large financial services customer, designing data governance frameworks (lineage, metadata, access controls) and hybrid/multi-cloud data solutions. Work spans graph databases, real-time streaming, vector databases, and secure data sharing for autonomous agents.
Germany: €148000 - €151000 (EUR) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
- Act as a primary technical point of contact for a large, complex financial services customer, building deep relationships with key stakeholders (CTOs, CDOs, Data Architects).
- Design and implement data governance frameworks, including data lineage, metadata management, access controls, and compliance with industry regulations (e.g., GDPR, CCPA, BCBS 239).
- Develop and advocate strategies for federating data responsibility across different business units and technical teams, enabling decentralized data ownership while maintaining centralized oversight and consistency.
- Design and implement data capabilities that seamlessly span across on-premises environments and multiple cloud providers, ensuring data portability, interoperability, and consistent access.
- Identify and address data requirements for emerging agentic technologies, such as real-time data streaming, vector databases, and secure data sharing for autonomous agents.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 7 years of experience in data architecture, data engineering, or a related field.
- 5 years of experience working with data platforms and technologies.
- Experience designing and implementing data solutions for enterprise customers with hybrid and multi-cloud in the financial markets industry.
- Experience with data modeling and graph databases (e.g., RDF or property graphs).
Preferred qualifications:
- Google Cloud certifications (e.g., Professional Data Engineer, Professional Cloud Architect).
- Experience designing and implementing data governance, security, and compliance in a highly regulated environment.
- Experience contributing to open-source data projects.
- Familiarity with machine learning and AI concepts and their application in data management and analysis.
- Knowledge of emerging agentic technologies and their implications for data architecture.