Principal Cloud Data Architect - Channels Data Platforms and Analytics

About the Role

The Principal Cloud Data Architect serves as the architectural authority for Channels Data Platforms and Analytics. This leader defines the target state architecture, drives modernization from legacy technologies to cloud-native platforms, and ensures security, resiliency, performance, and compliance across the data and analytics ecosystem. The role provides strategic and technical oversight for the Payment Tracker and guides the transformation of large-scale engineering teams and platforms, including mainframe-based reporting systems.

The Principal Cloud Data Architect will lead the architecture, modernization, and transformation of the Channels Data Platform, evolving it from on-prem data warehouses, Informatica ETL, Hadoop ecosystems, and legacy reporting workloads toward a cloud-native, scalable, and resilient architecture leveraging Azure, Databricks, Snowflake, Kafka, APIs/microservices, and modern engineering patterns.

Responsibilities

• Define and communicate the solution intent and architectural vision across Business, Data, Application, and Technology domains.
• Build and maintain a multi-year modernization roadmap for Channels Data Platforms, including mainframe, Hadoop, ETL, and analytics components.
• Establish target operating models, architectural patterns, and guardrails to support evolving capabilities and regulatory expectations.
• Drive enterprise alignment by collaborating with Enterprise Architecture, Platform Architecture, Information Governance, Risk, and Product.
• Lead transformation from Informatica, on-prem databases, Hadoop, and mainframe-based reporting into cloud-native architectures (Azure, Databricks/Delta, Snowflake, Event Hubs/Kafka).
• Define migration paths for mainframe jobs, batch interfaces, and legacy ledger/reporting logic into scalable modern architectures.
• Implement CI/CD for data, Infrastructure as Code (Terraform/Bicep), observability (logs/metrics/traces), and cost/performance governance.
• Ensure platform resiliency, scalability, and operational readiness (HA/DR, autoscaling, performance tuning, traffic management).
• Provide end-to-end architectural oversight for Payment Tracker, including UI, APIs/microservices, data models, analytics layers, and dashboards.
• Guide design for real-time and near real-time insights, data marts, and advanced analytics embedded in Payment Tracker experiences.
• Ensure adherence to NFRs (performance, security, maintainability, reliability) and integrated monitoring/alerting for application and data services.
• Lead design and code reviews; resolve architectural blockers; ensure compliance with the Bank’s Risk Framework, data privacy, entitlements, masking, and audit expectations.
• Partner with delivery teams to translate strategy into actionable technical backlogs and architecture epics.
• Drive the creation of reusable accelerators, libraries, templates, migration playbooks, and modernization frameworks.
• Mentor engineers and elevate engineering excellence across Channels Technology.
• Own R&D for the data and analytics portfolio: evaluate emerging tools, run POCs/Pilots, benchmark performance, publish decision records, and set technology adoption standards.
• Develop the engineering approach for the entire program/portfolio solution and work with Architecture to deliver the implementation of technical enablers.
• Lead the planning, definition, and design of complex features spanning multiple teams and explore solution alternatives.
• Create ideas on designing complex technology and solution development approaches.
• Lead technical oversight for teams in solution development, including design reviews and code within own domain.
• Define the technology tool stack for the solution within the range of internally approved and supported technologies.
• Explore state-of-the-art technologies to improve development efficiencies, quality of test/QA coverage, and release management.
• Lead and own the end-to-end test strategy, creation, adherence, and integration between teams for a program/portfolio solution.

Requirements

• 12+ years in data/software engineering with 8+ years designing enterprise data platforms or large distributed architectures.
• Demonstrated leadership in cloud modernization (Azure preferred), including Databricks (Spark/Delta), Snowflake, Kafka/Event Hubs.
• Strong background in modernizing legacy systems, including Informatica ETL, Hadoop/Big Data systems, and mainframe workloads (batch pipelines, reporting interfaces).
• Deep expertise in NFR-driven design: resiliency, security, performance, scalability, observability, and operational excellence.
• Strong proficiency in SQL and Python (Scala or Java a plus).
• Proven ability to influence senior leaders, drive enterprise alignment, and deliver outcomes in highly regulated environments.
• Strong communication skills—capable of translating complex engineering concepts for executive, business, and technical audiences.
• Experience with microservices, containers (Kubernetes/OpenShift), API gateways, and integration patterns.

Qualifications

Representative tools/technologies: Azure (ADLS Gen2, Event Hubs, Key Vault), Databricks, Snowflake, Informatica, Kafka, Mainframe/Z Series job orchestration, Oracle/Postgres, Python, SQL, Java/Scala (optional), Git, Azure DevOps/Jenkins, Docker/Kubernetes/OpenShift, Collibra, AppDynamics/Splunk/Grafana, Starburst.

Desired Qualifications

• Experience in Payments, Channels, CashPro, or analytics-driven applications.
• Knowledge of semantic layers (dbt, LookML), data quality frameworks (Great Expectations/Deequ), and data governance (Purview, Collibra).
• FinOps experience with cost optimization for cloud data workloads.
• Advanced understanding of streaming, event-driven architectures, and ML/AI integration.

Skills

• Automation
• Influence
• Result Orientation
• Stakeholder Management
• Technical Strategy Development
• Application Development
• Architecture
• Business Acumen
• Risk Management
• Solution Design
• Agile Practices
• Analytical Thinking
• Collaboration
• Data Management
• Solution Delivery Process

Schedule

1st shift (United States of America), 40 hours per week.