Senior Data Architect with Relational Graph Vector Architecture

Almatý
Astaná
Belgrado
Breslavia
Cluj-Napoca
Cracovia
Dnipró
Ereván
Járkov
Kyiv
Lárnaca
Leópolis
Lodz
Lublinie
Odesa
Remote.Bulgaria
Remote.Georgia
Remote.Kazakhstan
Remote.Poland
Riga
Sofia
Tiflis
Varna
Varsovia

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Project overview

This project focuses on building a next generation data foundation that combines relational storage, graph relationships, and vector embeddings to enable intelligent search and AI driven insights. The platform ensures that incoming expert content is instantly processed and made query ready within strict service level expectations.

Position overview

We are looking for a Senior Data Architect who will design and govern a unified relational, graph, and vector data ecosystem. You will work closely with the client’s data team to ensure data is structured, available, and optimized for advanced AI and search use cases. This role focuses on building scalable ingestion pipelines, enabling real time data synchronization, and maintaining high data quality across the full platform.

Technology stack

Google Cloud Platform, BigQuery, Cloud Spanner, Pub Sub, Dataflow, Vertex AI, vector databases, graph databases, Python, SQL, Apache Beam, IAM, encryption standards

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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