Manager & Data Engineer & Strategy Implementation

RBC; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading Canadian financial institution is seeking a Data Engineer to support its credit strategy modernization. This role involves designing and maintaining high-performance data pipelines using Python and PySpark while migrating legacy SAS processes. The ideal candidate has extensive experience in financial services and a growth mindset. This position offers the chance to work on impactful solutions for credit risk management and to collaborate with a high-performing technology transformation team.

Benefits

Ability to make a difference

Dynamic, collaborative environment

Challenging work opportunities

Qualifications

• 3+ years of hands-on data engineering experience, ideally in financial services.
• Advanced proficiency in Python and PySpark for data processing solutions.
• Strong SQL expertise with experience in big data platforms.

Responsibilities

• Build and optimize scalable data pipelines in Python and PySpark.
• Lead migration initiatives from legacy SAS to modern solutions.
• Architect data workflows for credit risk analytics.

Skills

Business Data Analysis

Communication

Credit Analysis

Critical Thinking

Database Queries

Data Visualization

Decision Making

Quantitative Methods

Risk Management

Tools

Python

PySpark

SQL

Job description

Job Description

Data Engineering role supporting RBC's credit strategy modernization. You'll design and maintain high-performance data pipelines as a core member of our technology transformation team. Your focus: migrating legacy SAS processes to Python and PySpark, while optimizing data processing across HDFS/Hive and AWS S3 platforms. This hands‑on technical position offers the opportunity to drive scalability, efficiency, and accuracy improvements in solutions that directly impact credit risk management across the organization.

What is the opportunity?

Data Engineering role supporting RBC's credit strategy modernization.

What will you do?

• Build and optimizescalable data pipelines in Python and PySpark, ensuring reliability and performance across HDFS/Hive and AWS S3 environments.
• Lead migration initiativestransforming legacy SAS processes into modern, cloud‑ready Python/PySpark solutions.
• Architect data workflowsthat support credit risk analytics and business intelligence at scale.
• Write production‑grade codewith rigorous testing, documentation, and adherence to software engineering best practices.
• Partner with data scientists and stakeholdersto translate business requirements into robust technical solutions.
• Manage code quality and collaborationthrough GitHub version control and peer review processes.
• Document technical infrastructureto enable team knowledge sharing and system maintainability.

What do you need to succeed?

Must have:

• 3+ yearsof hands‑on data engineering experience, ideally in financial services or credit risk environments.
• Advanced proficiency in Python and PySparkfor designing and optimizing large‑scale data processing solutions.
• Strong SQL expertisewith demonstrated experience in big data platforms (HDFS, Hive, or equivalent).
• Proven abilityto translate complex data requirements into clear, actionable solutions that drive business decisions.
• Software engineering discipline– writes clean, testable, and maintainable code with attention to quality and documentation.
• Growth mindset– committed to staying current with evolving data technologies and continuously raising technical standards.

Nice to have:

• Track record of solving ambiguous, high‑impact problemswith clear decision‑making and collaborative problem resolution.
• Excellent communication skills– ability to explain technical concepts clearly to both technical and non‑technical stakeholders.
• Background in financial services, particularly in credit risk, lending, or regulatory analytics.
• Experience with legacy systems and languages(SAS, TRIAD, BLAZE, or similar mainframe/proprietary platforms) – valuable for understanding existing processes during migration.

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high‑performing team
• Opportunities to do challenging work

Job Skills

Business Data Analysis, Communication, Credit Analysis, Critical Thinking, Database Queries, Data Visualization, Decision Making, Quantitative Methods, Risk Management

Additional Job Details

Address: RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: GROUP RISK MANAGEMENT

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-02-10

Application Deadline: 2026-02-24

Note

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

Inclusion and Equal Opportunity Employment

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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RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.