Principal Data Architect

GFT Poland is hiring for a role focusing on enterprise-scale data architecture and cloud transformation within the financial services domain.

• Extensive experience in Enterprise Data Architecture
• Strong knowledge of Data Lakehouse architecture including Bronze, Silver and Gold patterns
• Hands-on experience with GCP architecture design
• Strong expertise in BigQuery
• Experience in conceptual, logical and physical data modelling
• Knowledge of data governance frameworks and data quality management
• Experience with integration architecture and data lineage practices
• Understanding of GCP security and IAM concepts
• Experience working within Financial Markets or Surveillance domains
• Strong stakeholder management and communication skills

Nice to have:

• Experience with Market Abuse or Unauthorised Trading surveillance systems
• Knowledge of Vertex AI and machine learning platforms
• Experience with regulatory reporting or compliance initiatives
• Hands-on experience with Dataflow or Apache Beam
• Knowledge of Kubernetes (GKE)
• Experience with Terraform and CI/CD tooling
• Understanding of Java-based enterprise platforms

• Design enterprise-scale data architecture and target-state data platform solutions on GCP
• Define Bronze, Silver and Gold data lakehouse architecture patterns and standards
• Create conceptual, logical and physical data models for complex business domains
• Establish data governance frameworks, data quality controls and metadata standards
• Define integration architecture, data lineage and end-to-end data flows
• Collaborate with business and technology stakeholders to identify common data elements and enrichments
• Support the creation of analysis-ready datasets and reusable data products
• Provide architectural guidance for BigQuery-based solutions and cloud-native data platforms
• Assess cloud migration approaches and target-state architecture options
• Ensure alignment with security, IAM and regulatory requirements
• Contribute to architecture reviews, technical decision-making and best practices