Lead, Data Engineering - C$105,000 - C$155,000 A Year
Posted
Summary
A hands-on Data Engineering Tech Lead role on RBC Global Asset Management's Data & Analytics team: mentor a team of data engineers across squads, drive the data platform strategy, and design/maintain ETL pipelines and infrastructure using Hadoop/Spark/Kafka, SQL, Java/Scala/Python, Snowflake and cloud platforms to power BI, ML and AI.
What is the Opportunity?This is an opportunity within the Data & Analytics team at RBC Global Asset Management. We are seeking a hands‑on, highly skilled and motivated individual to join our dynamic team as a Data Engineering Tech Lead. As a key member of our data engineering team, you will play a crucial role in leading a team of talented data engineers to spearhead the delivery of data products to improve decision making, driven by data, and empowered by technology. Your primary focus will be on designing, implementing, and maintaining robust data infrastructure and pipelines to support our organization’s data needs and advance our capabilities pertaining to data engineering, BI, Machine Learning and AI.
What you will do:
Lead, mentor, and inspire a team of data engineers to achieve high performance levels.
Take on the role to lead a development team working as part of multiple squads.
Help drive our data strategy and modernise the data platform vision by designing and implementing scalable, maintainable and efficient data architectures.
Work closely with data architects to define data models and standards and ensure adherence to data engineering best practices.
Oversee the planning, execution, and delivery of data engineering projects.
Collaborate with cross‑functional teams to understand data requirements and deliver scalable solutions.
Develop and maintain robust ETL processes to extract, transform and load data from various sources into our data platform.
Optimise data integration workflows for performance and reliability.
Troubleshoot and resolve data integration issues.
Implement and enforce data quality standards and best practices while collaborating with data governance teams to ensure compliance with data policies and regulations.
Work closely with the data platform team to optimise data infrastructure, databases, storage and processing systems, and oversee the requirements to improve our DevOps, DataOps, MLOps processes and tools.
Apply design‑thinking and an agile mindset in working with various stakeholders to continuously experiment, iterate and deliver on solutions that enable end‑users to extract insights and value from data.
Stay informed about emerging technologies and trends in data engineering.
What you need:
5 years of hands‑on experience in a data engineering role and 2 years of leading a team of data engineers.
Hands‑on experience building batch and real‑time data pipelines leveraging big data technologies such as Hadoop, Spark, NiFi, Kafka, etc.
Proficiency in writing and optimizing SQL queries and at least one programming language such as Java, Scala or Python.
Experience with cloud‑based data platforms (Snowflake, AWS, Azure, GCP).
Experience with following DevOps and agile best practices.
Nice to have:
Experience with OpenShift, S3, Trino, Ranger and Hive.
Java Spring and MVC‑based web development concepts.
Knowledge of machine learning and data science concepts and tools.
Experience with event tracking, building workload monitoring dashboards.
What’s in it for you?
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 and geographies.
Job Skills
Big Data Management
Cloud Computing
Database Development
Data Mining
Data Warehousing (DW)
ETL Processing
Group Problem Solving
Quality Management
Requirements Analysis
Additional Job Details
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
Post date: 2026‑06‑29
Application Deadline: 2026‑07‑30 11:59 PM
Pay Range: $105,000 – $155,000
RBC is 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.
RBC is presently inviting candidates to apply for this existing vacancy. Qualified applicants may be contacted to review their resume in more detail.
What you will do:
Lead, mentor, and inspire a team of data engineers to achieve high performance levels.
Take on the role to lead a development team working as part of multiple squads.
Help drive our data strategy and modernise the data platform vision by designing and implementing scalable, maintainable and efficient data architectures.
Work closely with data architects to define data models and standards and ensure adherence to data engineering best practices.
Oversee the planning, execution, and delivery of data engineering projects.
Collaborate with cross‑functional teams to understand data requirements and deliver scalable solutions.
Develop and maintain robust ETL processes to extract, transform and load data from various sources into our data platform.
Optimise data integration workflows for performance and reliability.
Troubleshoot and resolve data integration issues.
Implement and enforce data quality standards and best practices while collaborating with data governance teams to ensure compliance with data policies and regulations.
Work closely with the data platform team to optimise data infrastructure, databases, storage and processing systems, and oversee the requirements to improve our DevOps, DataOps, MLOps processes and tools.
Apply design‑thinking and an agile mindset in working with various stakeholders to continuously experiment, iterate and deliver on solutions that enable end‑users to extract insights and value from data.
Stay informed about emerging technologies and trends in data engineering.
What you need:
5 years of hands‑on experience in a data engineering role and 2 years of leading a team of data engineers.
Hands‑on experience building batch and real‑time data pipelines leveraging big data technologies such as Hadoop, Spark, NiFi, Kafka, etc.
Proficiency in writing and optimizing SQL queries and at least one programming language such as Java, Scala or Python.
Experience with cloud‑based data platforms (Snowflake, AWS, Azure, GCP).
Experience with following DevOps and agile best practices.
Nice to have:
Experience with OpenShift, S3, Trino, Ranger and Hive.
Java Spring and MVC‑based web development concepts.
Knowledge of machine learning and data science concepts and tools.
Experience with event tracking, building workload monitoring dashboards.
What’s in it for you?
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 and geographies.
Job Skills
Big Data Management
Cloud Computing
Database Development
Data Mining
Data Warehousing (DW)
ETL Processing
Group Problem Solving
Quality Management
Requirements Analysis
Additional Job Details
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
Post date: 2026‑06‑29
Application Deadline: 2026‑07‑30 11:59 PM
Pay Range: $105,000 – $155,000
RBC is 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.
RBC is presently inviting candidates to apply for this existing vacancy. Qualified applicants may be contacted to review their resume in more detail.