Job purpose
We are seeking a tenured Data Architect to lead end-to-end data solution design, define current and target state architectures, conduct schema reviews, and shape enterprise reporting capabilities across regulatory, risk, finance, and trading domains. The ideal candidate will drive enterprise data governance, lineage, modernization, and cloud transformation initiatives while enabling scalable, resilient, and compliance-ready data platforms leveraging modern data engineering practices and medallion architecture principles.
The role will provide strategic guidance on cloud migration and modernization pathways across Azure, GCP, and Databricks, while advancing self-service analytics, scalable data warehousing, and enterprise integration capabilities. The candidate will collaborate closely with architecture, engineering, DevOps, QA, business, and operations teams to deliver secure, high-performing, and reliable data platforms that accelerate business insights, regulatory reporting, and operational efficiency.
Key responsibilities
- Lead end-to-end enterprise data architecture and solution design across regulatory, finance, risk, treasury, and trading domains.
- Define current-state and target-state data architectures, modernization roadmaps, and migration strategies.
- Design scalable, modular, cloud-native data platforms leveraging Azure, AWS, Databricks, Data Lakes, and medallion architecture patterns.
- Architect and govern modern ETL/ELT, orchestration, streaming, event-driven, and batch processing frameworks using technologies such as Apache Airflow and Databricks Workflows.
- Conduct detailed schema reviews, data model assessments, and architecture governance activities across enterprise platforms.
- Define and govern enterprise data models, canonical data structures, and integration standards.
- Lead modernization of legacy SQL Server, SSIS, SSRS, SSAS, and monolithic reporting ecosystems.
- Establish enterprise-wide data governance, metadata management, lineage, auditability, reconciliation, and data quality frameworks.
- Ensure compliance with regulatory and banking requirements including MiFID II, EMIR, SFTR, FCA, and other compliance-driven reporting obligations.
- Design scalable reporting and semantic layer architectures supporting enterprise reporting and self-service analytics.
- Review reporting wireframes, dashboard designs, and analytical data consumption patterns.
- Define observability, resiliency, HA/DR, RTO/RPO, SLA/SLO, and operational monitoring standards for enterprise data platforms.
- Collaborate with engineering and DevOps teams to establish CI/CD, automation, infrastructure-as-code, and deployment governance patterns.
- Improve operational resilience by reducing manual interventions, SME dependencies, and tightly coupled architectures.
- Partner with business, operations, finance, risk, and compliance stakeholders to align architecture with strategic and operational objectives.
- Support enterprise data platform scalability, performance optimization, partitioning, archival, and lifecycle management strategies.
- Drive adoption of reusable integration patterns, APIs, messaging architectures, and modern data platform best practices.
Key competencies
- Strong enterprise data architecture capability with experience defining target-state architectures, modernization roadmaps, and scalable data platform strategies.
- Deep understanding of cloud-native data ecosystems, distributed processing frameworks, data lakes, medallion architecture, Apache Airflow, Databricks Workflows, and modern data engineering practices.
- Strong expertise in data warehousing, dimensional modelling, ETL/ELT frameworks, metadata management, lineage, reconciliation, and enterprise data governance.
- Proven ability to modernise complex legacy and monolithic data environments into scalable, resilient, and modular architectures.
- Strong understanding of financial services, capital markets, regulatory reporting, and compliance-driven data architectures.
- Expertise in designing highly available, scalable, secure, and performance-optimized enterprise data platforms.
- Strong knowledge of integration patterns including APIs, messaging systems, event-driven architectures, MQ, FIX, gRPC, and file-based integrations.
- Ability to define and implement enterprise-wide data quality, observability, auditability, and operational resilience frameworks.
- Excellent analytical, problem-solving, and architecture governance skills with the ability to evaluate complex technical and business trade-offs.
- Strong stakeholder management and communication capability with experience working across business, operations, risk, compliance, engineering, and leadership teams.
- Experience collaborating within agile, DevOps, and cross-functional delivery environments.
- Strong documentation, presentation, and architecture review skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
- Ability to drive self-service analytics, reporting modernization, and scalable data consumption strategies across enterprise platforms.
- Strong understanding of operational resilience, disaster recovery, RTO/RPO, SLA/SLO management, and enterprise platform scalability considerations.
