Principal Data Architect

WHAT IS THE OPPORTUNITY?

As a Principal Data Architect at RBC, you will drive forward a culture of data engineering excellence, innovation, and productivity within our data and analytics teams. You will be pivotal in developing patterns and setting both architecture and technology standards to ensure RBC architects robust, scalable, and future‑proof data solutions. Your role will focus on Enterprise architecture for our Enterprise Data Lake (EDL) and Enterprise Data Warehouse (EDW) ecosystems, partnering with the data engineering and application development teams to create target state architectures, improve data processes, streamline data pipelines, and ultimately drive the creation of high‑quality, valuable data solutions.

You will need to be opinionated in ensuring the right technology solutions are selected and/or built, focusing on core strategic platforms and ensuring a high degree of standardization and reuse.

This role will also help provide Enterprise Architecture Governance for AI and Data initiatives across the bank, as well as drive forward on strategic architecture goals and leading modernization efforts such as the creation of the RBC Well‑Architected Framework, maintaining our technology reference model and ensuring necessary data patterns are available for the organization.

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• Drive the adoption of best practices in data architecture, data modeling, and data engineering processes with a focus on enterprise reuse, developer experience, innovation, and productivity.
  
• Collaborate closely with stakeholders, solution architects, data scientists, and engineering teams to understand data needs, propose solutions, and ensure alignment with strategic goals.
  
• Lead initiatives to evaluate and introduce new tools, technologies, and frameworks that can enhance our data lifecycle and deliver competitive advantages.
  
• Advocate for and contribute to the creation of maintainable, scalable, and future‑proof data architectures, patterns, and standards for EDL and EDW.
  
• Facilitate workshops and discussions to effectively convey data architecture principles and strategies across the enterprise.
  
• Ensure continuous attention to data engineering excellence, good design, and governance, thereby driving agility and productivity.
  
• Simplify data processes and systems, maximizing throughput, and removing bottlenecks to data engineering productivity while adhering to governance and compliance standards.
  
• Provide mentorship and guidance to data engineers and architects, fostering a culture of learning and growth.
  
• Stay abreast of industry trends and emerging technologies in data architecture, assessing their applicability to our goals and objectives.
  

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• Bachelor’s degree in Computer Science, Data Engineering, or a related field.
  
• Extensive experience in data architecture with a proven track record of innovation and productivity improvements in EDL/EDW environments.
  
• Proficiency in data modeling, ETL/ELT processes, and technologies such as Hadoop, Spark, Snowflake, Databricks, or similar platforms.
  
• Excellent interpersonal and communication skills, with the ability to lead cross‑department initiatives and interact effectively with stakeholders at all levels.
  
• Demonstrated ability to mentor and coach teams toward achieving their highest potential.
  
• Experience with DevOps practices, continuous integration, and continuous delivery (CI/CD) pipelines for data engineering.
  
• Good understanding of Agile methodologies and principles, particularly those emphasizing collaboration, responsiveness to change, and customer focus.
  
• Expert‑level critical thinking.
  
• Ability to step back and view the macro landscape for strategy architecture.
  
• Good understanding of development practices.
  

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• Understanding of data security principles and practices, including experience with data encryption, masking, and governance frameworks.
  
• Experience with performance tuning, optimization, and monitoring of data pipelines and systems.
  
• Familiarity with Generative AI and Large Language Models, and their application in data engineering to drive productivity and innovation.
  
• Knowledge of cloud‑based data platforms (e.g., AWS, Azure, GCP) and their native data services.
  
• Enterprise architecture experience.
  
• Solution architecture experience.
  

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• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
  
• Leaders who support your development through coaching and managing opportunities.
  
• Ability to make a difference and lasting impact.
  
• Work in a dynamic, collaborative, progressive, and high‑performing team.
  
• A world‑class training program in financial services.
  
• Flexible work/life balance options.
  
• Opportunities to do challenging work.
  

Applications Architecture, Architecture Principles, Critical Thinking, Data Architecture, Data Architecture Principles, Data Engineering, Data Lifecycle, Decision Making, Enterprise IT Architecture, Information Technology Consulting, IT Architecture, Multi‑Level Communication, Service Oriented Architecture (SOA), Target Architecture

Address: 100 BISHOPSGATE:LONDON

City: London

Country: United Kingdom

Work hours/week: 35

Employment Type: Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2025-11-04

Application Deadline: 2025-11-16

Applications will be accepted until 11:59 PM on the day prior to the application deadline date above.

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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