Senior Data Architect

Key Responsibilities

• Understand Data Requirements & Authoritative Data Source Assessment: Engage early to capture business and technical data needs.
• Create and Maintain Architecture Artifacts
• Data Flow Diagrams (DFD) and Logical/Physical Data Models for end-to-end lineage.
• Data Dictionary: Define entities, attributes, naming conventions, encryption/tokenization requirements, and traceability for compliance.
• Data Mapping Sheets: Document source-to-target mappings, lineage, and transformation logic for all critical flows.
• Data Privacy Impact Assessment (DPIA) for sensitive data projects.
• Update Architecture Vision and Security Components: Ensure alignment with AVD (Architecture Vision Delta) and security design decisions.
• Design and Implement Data Solutions
• Design & Build scalable pipelines (Batch and real-time) using cloud-native tools/frameworks (DIHOP, DIHOC, AWS Glue, DBT, Snowflake, Databricks).
• Apply architectural patterns for data lakes, streaming, and batch processing.
• Exposure to cloud technologies – Snowflake, Redshift, Apache Flink and Apache Kafka.
• Technical POCs
• Technical assessment of Cloud data technologies to leverage considering Fraud Business and technical requirements
• Design, execute and lead POC’s involving Cloud technologies to validate/support the assessment.
• Ensure Compliance with Data Standards: Apply Barclays Data Architecture Capability Directives and DACM patterns for governance and quality.
• Integrate Security and Privacy Controls: Tokenization, masking, and encryption for PII/PCI data across ingestion and storage layers.

Role

Senior Data Architect

Experience

10 years

Location

Northampton, UK

Work mode

Hybrid

Data Architecture & Engineering Deliverables

• Understand Data Requirements & Authoritative Data Source Assessment: Engage early to capture business and technical data needs.
• Create and Maintain Architecture Artifacts
• Data Flow Diagrams (DFD) and Logical/Physical Data Models for end-to-end lineage.
• Data Dictionary: Define entities, attributes, naming conventions, encryption/tokenization requirements, and traceability for compliance.
• Data Mapping Sheets: Document source-to-target mappings, lineage, and transformation logic for all critical flows.
• Data Privacy Impact Assessment (DPIA) for sensitive data projects.
• Update Architecture Vision and Security Components: Ensure alignment with AVD (Architecture Vision Delta) and security design decisions.

Cloud & Platform Responsibilities

• Design and Implement Data Solutions
• Design & Build scalable pipelines (Batch and real-time) using cloud-native tools/frameworks (DIHOP, DIHOC, AWS Glue, DBT, Snowflake, Databricks).
• Apply architectural patterns for data lakes, streaming, and batch processing.
• Exposure to cloud technologies – Snowflake, Redshift, Apache Flink and Apache Kafka.
• Technical POCs
• Technical assessment of Cloud data technologies to leverage considering Fraud Business and technical requirements
• Design, execute and lead POC’s involving Cloud technologies to validate/support the assessment.
• Ensure Compliance with Data Standards: Apply Barclays Data Architecture Capability Directives and DACM patterns for governance and quality.
• Integrate Security and Privacy Controls: Tokenization, masking, and encryption for PII/PCI data across ingestion and storage layers.

Governance & Approvals

• Liaise with Lead Architects Guild and Control Tribes
• Present artifacts for review and sign-off in forums like TAC, EDP ARB, and Fraud Design Authority.
• Secure Mandatory Approvals: CAF1 (Non-Prod) and CAF2 (Prod) for environment readiness.
• CARA, DPIA and DARB for architecture compliance.

Collaboration & Lifecycle Support

• Work with Solution Architects and Engineering Teams
• Assist in solution design, low-level design, and component build.
• Support SIT, OAT, and E2E testing phases for data integrity and performance.
• Service Transition & RTB Handover: Ensure smooth deployment and operational readiness for production environments.

Continuous Improvement & Standards

• Define and Enhance Standards: Contribute to Data Dictionary and Data Mapping standards and aide-memoires for consistency.
• Participate in Architecture Working Groups: Drive adoption of reusable patterns, accelerators, and compliance frameworks.
• Works closely with CTO, CDO and other Solution Architects to deliver Fraud solutions at highest standards.
• Responsible for designing, sustaining & enhancing Fraud data architecture.
• Responsible for hands‑on design and implementation of integrated Fraud based data solutions that are scalable, built for rapid change and meets functional and non‑functional requirements.
• Assist in planning, architecture, analysis, and design of applications and integrate with legacy systems.

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