Staff Data Engineer

RBC•Toronto, ON

1d•Onsite

About The Position

We're looking for an experienced Data Engineer who will bring focus and subject-matter expertise around designing and building robust, distributed, and scalable data applications in a real-time and big data context. This is a unique opportunity to grow in the world of modern data engineering and work with a team of passionate individuals committed to the mission of delivering cutting-edge data solutions to the enterprise. At RBC Borealis, you'll be joining a team focused on building cutting-edge data applications that provide a centralized view of all interactions and empower the enterprise with real-time decisioning capabilities. You will support existing platforms while helping develop next-generation data functionality that drives impact for our clients across the bank.

Requirements

Strong and relevant experience designing and implementing data intensive real-time systems.
Strong software development experience with tech stack: Java, Kafka, NiFi, Flink, DBT, Kubernetes, Hive.
Working with building and maintaining DevOps pipeline (GitOps) and orchestration tools such as Airflow, Dagster, Stonebranch.
Hands-on experience building and deploying hybrid environments on-prem and major cloud environments, such as AWS and Azure.
Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management.
Attention to detail with strong time management and project planning skills.
Excellent interpersonal and communication skills including presentation and conflict resolution.

Nice To Haves

Experience in building agentic workflows is a plus.
Experience in financial services with a high-level understanding of the Banking domain is a plus.

Responsibilities

Developing Java based solutions to solve complex problems using real-time data and historical data sets.
Deploying data processes, pipelines, and algorithms to RBC Infrastructure.
Responsible for every step of the data process from data ingestion, management, architecture, transformation, and integration.
Providing support to existing applications in Production, focusing on timely resolution of issues and ensuring smooth running of all applications.