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. Lead, mentor, and inspire a team of data engineers to achieve high performance levels. 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. 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. 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. A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable. Flexible work/life balance options.

Big Data Management Database Development Data

Mining Data Warehousing (DW) Quality Management Requirements Analysis Employment Type: Full time 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 chance for all.

📌 Lead Data Engineer BI Big Data (Toronto)
🏢 RBC
📍 Toronto