Staff Data Engineer

Job Title: Staff Data Engineer Company: RBC Job Category: Machine Learning Roles & Responsibilities: Job Description RBC Wealth Management (WM) Data \& AI is responsible for driving data driven decision making end\-to\-end across our global businesses. We're modernizing our data architecture, building out BI and analytics capabilities, and developing cutting\-edge AI/ML solutions—from traditional machine learning to Generative AI—to support our Global Executive Leadership as well as our Digital and Global Investment teams. * Architect, establish, maintain, and evolve the data foundation and analytical environments that support BI/analytics workloads and downstream AI/ML consumers with high performance and reliability * Design, build, and maintain scalable, production\-grade data pipelines that ingest, transform, and serve both structured and unstructured data across WM LoBs * Design data models and schemas that serve multiple consumer types—BI dashboards, reporting, and downstream ML pipelines—balancing performance, flexibility, and reusability * Build and maintain APIs and integrations that expose data to downstream consumers, including AI/ML systems and business workflows * Define clean data contracts and interfaces with downstream AI/ML and BI teams—schemas, SLAs, and freshness guarantees—to ensure reliable handoffs * Implement monitoring, logging, and observability for data pipelines to ensure reliability, performance, and compliance * Optimize pipeline and storage performance and cost (e.g., query tuning, partitioning, compute/storage cost management) across Dev, UAT, and Production environments * Create, maintain, and develop data assets across Dev, UAT, and Production environments, ensuring consistency * Identify, source, stage, and model improvements to partially/completely automate the most common, repeatable and tedious manual data preparation and integration tasks, and optimize data delivery for greater scalability, as part of the end\-to\-end data lifecycle * Implement data quality frameworks, automated testing, and monitoring to ensure data integrity and trust across all downstream consumers * Support data cataloging and metadata management practices to ensure data assets are discoverable, well\-documented, and governed * Support DevOps and DataOps best practices, including CI/CD, infrastructure\-as\-code, and automated testing across data pipelines * Use version control systems (e.g., GitHub) and data/schema comparison tooling to manage code and data changes safely across environments * 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 * Flexible work/life balance options * Opportunities to do challenging work * Opportunities to take on progressively greater accountabilities * Access to a variety of job opportunities across business Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Quality Management, Requirements Analysis, Waterfall ModelAdditional Job Details WEALTH MANAGEMENTJob Type: At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One 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. Work Location: Toronto, ON, Canada Availability: Full time

* Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related technical field * 5\+ years of professional experience in data engineering or related roles * Strong programming skills in Python and SQL, with hands\-on experience building and optimizing APIs and data pipelines at scale * Deep experience with modern data platforms and tools such as Databricks, Snowflake, Spark, and cloud\-native data services (AWS, Azure, or GCP) * Solid understanding of data warehousing, data lakehouse architectures, and data modelling concepts—and when to apply each * Knowledge of and experience implementing medallion (bronze/silver/gold) architecture patterns for structuring data lakehouse layers * Experience designing data models and pipelines that serve multiple consumer types (e.g., BI/reporting and downstream ML use cases) * Proficiency with DevOps/DataOps practices and CI/CD tooling (e.g., GitHub Actions, Jenkins, Azure DevOps) for data pipelines * Experience with automated unit testing methodologies for data pipelines and transformations * Strong experience with data governance, data quality, and data security best practices * Passion for problem\-solving and tackling challenges in real\-world contexts, leveraging large\-scale datasets and modern data approaches Key Skills: Machine Learning, Python Salary: Not disclosed