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Prospect

We are seeking a talented Data Engineer to join our rapidly expanding Centralized Data Hub. This strategic initiative transforms how our organization manages and leverages data at scale, and as a key contributor you will help build the backbone for enterprise‑wide data operations.

What Makes This Opportunity Unique

- Cutting‑Edge Tech Stack: work with modern tools and frameworks, implementing industry best practices in data architecture, streaming and batch processing.
- High‑Impact Project: play a pivotal role in a high‑visibility, heavily invested project that receives executive attention.
- Career Acceleration: gain hands‑on experience with modern data engineering patterns, Lambda architecture and distributed systems at scale.
- Innovation‑Driven Culture: join a team that prioritizes code quality, automation and continuous improvement.

Key Responsibilities

- Build scalable data pipelines and integration frameworks.
- Design and implement robust data models and schemas.
- Develop real‑time streaming and batch processing solutions.
- Establish data governance and quality standards.
- Collaborate with cross‑functional teams to deliver data‑driven solutions.

Qualifications

Must‑have

- Education:



degree in Computer Science or a related field preferred.
- Proficiency in Python and object‑oriented development.
- Experience with NoSQL databases (MongoDB) and relational databases.
- Hands‑on experience with Apache Kafka for streaming data.
- Familiarity with data pipeline orchestration tools (Dagster, Airflow, Luigi, etc.).
- Experience with containerization and orchestration tools (Docker, Kubernetes).
- Proficiency with Git version control.

Nice to have

- Experience with Apache Hadoop, YARN, and Spark.
- Experience with Polars or Pandas.

Benefits

- Participate in fun events and gamification challenges to build your career toolkit while enjoying work‑life balance.
- Leaders who support your development through coaching and learning opportunities.
- Work in a dynamic, collaborative, progressive and high‑performing team.
- Ability to make a significant, lasting impact.
- Enjoy a comfortable, casual work environment.

Location: RBC Waterpark Place, 88 Queens Quay W, Toronto, Canada.

Work hours: 37.5 hours per week. Employment type: Full time. Pay type: Salaried.

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Apply on Kit Job: kitjob.ca/job/2frzyp

📌 Data Engineer (Toronto)
🏢 RBC
📍 Toronto