Senior Data Engineer

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

Benefits offered by this job

Total Rewards program with bonuses and

Flexible benefits

World-class training program

Flexible work/life balance

Job summary

RBC in Toronto, Canada, seeks a Lead Data Engineer to design and maintain scalable data pipelines for analytics and reporting. You will implement end-to-end data pipeline architecture, ensure data quality, and collaborate with analysts to build robust data models.

Responsibilities include building pipelines with dbt, crafting optimized SQL, monitoring production jobs, and contributing to Agile processes. Strong Python/PySpark and AWS skills required; experience with Snowflake and Airflow is a

Qualifications

• 3+ years hands-on data engineering experience.
• Proficiency in Python/PySpark, SQL, and building ETL pipelines.
• Experience with AWS data services, Snowflake and dbt.
• Familiarity with Airflow and data modeling concepts.

Responsibilities

• Design, implement and maintain data ingestion and transformation pipelines.
• Build transformation models and data pipelines using dbt.
• Develop optimized SQL transformations for large datasets.
• Implement data quality checks and validation logic within ETL pipelines.
• Monitor data pipelines and troubleshoot production issues.
• Collaborate with data analysts and architects to design scalable data models.
• Document data lineage, transformations, and technical architecture.
• Participate in Agile development processes and code reviews.

Skills

Python/PySpark

SQL

ETL pipelines

AWS (S3/Glue/Lambda/Redshift)

Snowflake

dbt

Airflow

Tools

Kotlin

Job description

Job Description

We are seeking a Lead Data Engineer to build and maintain scalable data pipelines supporting analytics and reporting. The engineer will follow end-to-end process standards and guidelines to ensure accurate and efficient build out of data pipeline architecture within project timeframes.

What will you do?

• Design, implement and maintain data ingestion and transformation pipelines.
• Build transformation models and data pipelines using dbt.
• Develop optimized SQL transformations for large datasets.
• Implement data quality checks and validation logic within ETL pipelines.
• Monitor data pipelines and troubleshoot production issues.
• Collaborate with data analysts and architects to design scalable data models.
• Document data lineage, transformations, and technical architecture.
• Participate in Agile development processes and code reviews.

What do you need to succeed?

Must have:

• 3+ years of hands-on data engineering experience.
• Strong technical proficiency in:
• Python: Production-quality code for data pipelines, automation, and scripting, including PySpark.
• SQL: Advanced query writing, optimization, indexing, stored procedures.
• ETL: Utilizing DataFrames for building programmatic ETL data pipelines.
• AWS: S3, Glue, Lambda, Redshift, Cloudwatch.
• Snowflake: Data warehousing, virtual warehouses, clustering, security.
• dbt: Model development, testing, documentation, incremental builds.
• Familiarity with data orchestration tools (Airflow).
• Demonstrated ability to work independently, take ownership, and drive projects to completion.
• Excellent problem-solving skills and attention to detail.

Nice-to-have:

• Knowledge of data streaming platforms or queues (Apache Kafka, AWS Kinesis, RabbitMQ)
• Experience in building Kotlin, Spring boot and Java applications.
• Familiarity with Parquet formatting to maximize I/O performance and storage efficiency across data lakes.

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
• A world-class training program in financial services
• Flexible work/life balance options
• Opportunities to do challenging work

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: 20 KING 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: 2026-09-17
• Application Deadline: 2026-10-02

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.