Manager, Data and Analytics Engineer

rbc; Toronto; On-site; CAD 110,000 - 150,000; Full time

Job summary

RBC is seeking a Manager, Data and Analytics Engineer to transform how data informs business insights, reporting, and decisions. The role spans data engineering, analytics, and business teams to build reliable pipelines and analytics datasets for faster access and clearer insights.

You will solve data challenges by improving data collection and transformation, automating processes, and laying the foundation for enhanced analytics and reporting.

Qualifications

• 3+ years of experience in data analytics, data engineering, or related roles.
• Strong Python skills for data manipulation and automation.
• Experience with data-processing frameworks (Pandas/Polars/PySpark) for large datasets.
• Hands-on ETL/ELT pipeline development and scheduling/orchestration tools.
• Understanding of data quality, testing, validation, and troubleshooting.
• Excellent communication with technical and business stakeholders.

Responsibilities

• Build and maintain ETL/ELT pipelines aggregating data from multiple sources.
• Use Python and SQL to extract, transform, and validate data.
• Investigate data issues and coordinate with source-system teams to resolve.
• Develop and maintain scheduled data workflows with monitoring and testing.
• Create clean, reusable analytical datasets to support reporting and decision-making.
• Implement data-quality checks to improve data reliability.
• Automate manual data and reporting processes to boost speed and efficiency.
• Partner with analytics and business stakeholders to translate requirements into data solutions.

Skills

Python

Data manipulation

ETL/ELT pipelines

Data quality & validation

Pandas/Polars/PySpark

SQL

Communication with stakeholders

Tools

Tableau

Cloud platforms

Job description

What is the opportunity?

As Manager, Data and Analytics Engineer, you are responsible for transforming how data is used to drive business insights, reporting and decision‑making.

You will have the opportunity to work across data engineering, analytics and business teams to build reliable data pipelines and analytical datasets that make information faster, more accessible and easier to use.

This role is ideal for someone who enjoys solving problems with data - from improving the way data is collected and transformed, to automating processes and creating the foundation for better analytics and reporting.

What will you do?

• Build and maintain ETL/ELT pipelines that bring together data from multiple sources.
• Use Python and SQL to extract, transform, validate and manipulate data.
• Investigate data issues, identify root causes and work with technology/source-system teams to resolve them.
• Develop and maintain scheduled data workflows, including monitoring, testing and troubleshooting.
• Create clean, reusable analytical datasets that support reporting, analytics and business decisions.
• Implement data-quality checks and improve the accuracy, consistency and reliability of data.
• Automate manual data and reporting processes to improve speed and efficiency.
• Partner with analytics and business stakeholders to understand requirements and translate them into data solutions.

What do you need to succeed?

Must Have

• 3+ years of experience working with data, analytics or data engineering.
• Strong Python skills, particularly for data manipulation and automation.
• Experience with Pandas/Polars/PySpark or similar data-processing frameworks to work with large or complex data sets
• Hands-on experience building or maintaining ETL/ELT pipelines, with experience in scheduling/orchestration tools and production data workflows.
• Understanding data quality, testing, validation and troubleshooting.
• Communicate effectively with both technical & business stakeholders and translate business requirements into practical data solutions.

Nice to Have

• Experience with Tableau or other BI/reporting tools.
• Experience with cloud data platforms or modern data architectures.
• Experience in financial services, finance or accounting.
• Exposure to machine learning, generative AI or agentic workflows.

Job Skills

Data Analytics, Data Automation, Data Engineering, Data Pipelines, Extract Transform Load (ETL), Pandas (Software), Python (Programming Language), Structured Query Language (SQL)

Additional Job Details

Address:
180 WELLINGTON ST W:TORONTO City:
Toronto Country:
Canada Work hours/week:
37.5 Employment Type:
Full time Platform:
TECHNOLOGY AND OPERATIONS Job Type:
Regular Pay Type:
Salaried Posted Date:
2026-09-24 Application Deadline:
2026-10-10 Note : Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

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.

Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com .