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A leading financial services firm in Toronto is seeking a Principal Engineer to modernize quantitative investment platforms. You will design cloud-native data architectures, support machine learning initiatives, and develop scalable analytics pipelines. Ideal candidates have strong expertise in cloud platforms and experience in quantitative research environments. This full-time role offers a dynamic work environment and competitive compensation in a collaborative team.
RBC Global Asset Management (GAM) is seeking a Principal Engineer to support the modernization of our quantitative investment platforms. This role is crucial in developing a modern, cloud-native data architecture to enhance our research capabilities. As a hands‑on engineering leader, you will enable machine learning, scalable analytics, and data processing, supporting faster time to insight for our quantitative investment team.
Lead the design and implementation of scalable data, analytics, and machine learning pipelines. Support the transition of analytical workflows from existing tools to Azure Databricks.
Partner directly with Quantitative Investment and Research teams to enable alpha research, portfolio engineering, and machine learning at scale.
Drive change management efforts by developing training programs, creating comprehensive documentation, and facilitating the smooth adoption of new analytical workflows.
Construct robust data processing pipelines capable of handling large‑scale financial datasets with improved performance, reliability, and analytical flexibility.
Define and implement best practices for an integrated, modern data platform, ensuring data quality, security, and compliance with enterprise and regulatory requirements.
Strong technical background with expertise in cloud platforms (e.g. Azure, Databricks), data engineering, data modelling, and modern analytics tools essential for building scalable research infrastructure.
Proficiency in Python, SQL, Spark, and other big data technologies necessary for supporting advanced quantitative research workflows.
Excellent ability to work effectively with quantitative researchers, translating business requirements into technical solutions while building consensus across teams.
Experience with machine learning and AI applications, preferably with investment management, particularly in developing and deploying quantitative investment models.
Proven track record of applying AI / ML tools to solve high‑impact business problems, with quantified business results.
Familiarity with the investment industry, particularly in asset management and quantitative investing.
Knowledge of MatLab, Bloomberg APIs, or similar tools commonly used in quantitative research environments.
Advanced technical certifications in cloud technologies (Azure, Databricks, Snowflake) or relevant degrees in quantitative fields (Computer Science, Mathematics, Finance).
Understanding of regulatory requirements and risk management frameworks in investment management, including experience with data governance and compliance.
Strong cross‑functional collaboration experience with product managers, security, compliance, privacy, legal, DevOps, and other teams, demonstrating excellent written and verbal communication skills to influence both technical and non‑technical stakeholders.
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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Analytics, Big Data, Big Data Management, Business Analysis, Business Problems, Cloud Computing, Data Architecture, Database Development, Data Engineering, Data Mining, Data Modeling, Data Warehousing (DW), ETL Processing, Group Problem Solving, Machine Learning (ML), Quality Management, Quantitative Investment, Requirements Analysis, Unstructured Data
Address :
RBC CENTRE, 155 WELLINGTON ST W : TORONTO
City : Toronto
Country : Canada
Work hours / week : 37.5
Employment Type : Full time
Platform : WEALTH MANAGEMENT
Job Type : Regular
Pay Type : Salaried
Posted Date : 2025-11-10
Application Deadline :
Note : Applications will be accepted until 11 : 59 PM on the day prior to the application deadline date above