Senior Data Architect with Relational Graph Vector Architecture
- Ałmaty
- Astana
- Belgrad
- Charków
- Dnipro
- Erywań
- Kijów
- Kluż-Napoka
- Kraków
- Larnaka
- Łódź
- Lublin
- Lwów
- Odesa
- Remote.Bulgaria
- Remote.Georgia
- Remote.Kazakhstan
- Remote.Poland
- Ryga
- Sofia
- Tbilisi
- Warna
- Warszawa
- Wrocław
Jeśli otrzymałeś tę ofertę pracy od naszych rekruterów, zapoznaj się z naszą Polityką prywatności.
Project overview
Position overview
Technology stack
Responsibilities
- Design a unified data architecture that combines relational, graph, and vector data models
- Define and implement data governance frameworks including data lineage, data quality, and versioning
- Design and establish scalable ingestion pipelines to support near real time data processing and synchronization
- Develop change data capture strategies and define triggers for re vectorisation and graph updates
- Ensure data consistency and integrity across relational, graph, and vector components
- Translate business and analytical requirements into data models, mappings, and processing logic
- Configure identity and access management and enforce encryption standards for secure data handling
- Collaborate with engineering teams to ensure scalability, reliability, and observability of data pipelines
- Support monitoring and validation processes to ensure production ready data outputs
Requirements
- Experience designing data platforms, not only data pipelines
- Strong background in data governance, data lineage, and data quality practices
- Experience with real time data processing and synchronization, including change data capture
- Experience working with graph architectures and or vector based data systems
- Proficiency in SQL and Python for data processing and pipeline development
- Experience with Google Cloud Platform services such as BigQuery, Cloud Spanner, Pub Sub, and Dataflow
- Understanding of data security practices including IAM configuration and encryption standards
- Ability to translate business requirements into technical data architecture and solutions
- Experience collaborating with cross functional technical teams and supporting active development environments
Nice to have
- Experience with vector databases and embedding lifecycle management
- Familiarity with graph data modeling and graph query languages
- Experience with Apache Beam or similar distributed processing frameworks
- Exposure to AI or machine learning driven data platforms
- Experience with observability tools for monitoring pipeline performance and reliability
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