Lead Data Engineer, GFT

RBC; Toronto; On-site; CAD 150,000 - 190,000; Full time

Benefits offered by this job

Total Rewards Program

Bonuses

Flexible benefits

Stock options

Competitive compensation

Job summary

RBC is seeking a Lead Data Engineer to drive the Finance Data Platform within the DaaS team. You will lead design, development and governance of end-to-end data pipelines on public cloud infrastructure, enabling analytics and reporting across financial datasets.

You will collaborate with Architecture, Business SME and Data Stewards, building scalable data solutions, and ensuring data quality and security using best practices across the data lifecycle.

Qualifications

• Undergraduate degree/diploma in computer science/engineering or related technology discipline.
• 7+ years of experience in data engineering with at least 3 years in system integration, data engineering and cloud architecture.
• Experience with cloud platforms and data tools listed above.
• Strong data governance, SQL, and data transformation skills.
• Experience with generative AI tools/technologies.

Responsibilities

• Lead end-to-end data platform design, data sourcing, lineage, transformation and storage.
• Design, develop and support data pipelines and ETL frameworks.
• Communicate data modeling and architecture strategies to cross-functional teams.
• Implement internal process improvements and data enrichment for analytics.
• Ensure data processing accuracy and reliable reporting.

Skills

Data engineering

Cloud architecture

SQL

Generative AI

Data governance

Data modeling

ETL frameworks

Python/Scala/Java

Communication

Multi-tasking

Education

Undergraduate degree/diploma in computer science/engineering or related technology discipline

Tools

Cloudera Data Platform

Microsoft Azure

AWS

DBT

Databricks

Snowflake

Apache Airflow

Stonebranch UAC

Control‑M

OpenShift

Docker

Kubernetes

FastAPI

LDAP

Kerberos

OAuth 2.0

Microsoft Entra ID

HashiCorp Vault

GitHub Actions

Job description

What is the opportunity?

As Lead Data Engineer in the Data as a Service (DaaS) Team within Global Functions Technology, you will provide technical leadership and execution of development deliverables for the reimagined Finance Data Platform. The platform, leveraging public cloud infrastructure, will serve as the central repository of finance related datasets, with capabilities including the acquisition, standardization, enrichment, and provisioning, of positional/trade, sub‑ledger and general‑ledger trial balances, and reference data, and include capabilities supporting reconciliation, analytics, and reporting functions.

Job Description

What is the opportunity?

As Lead Data Engineer in the Data as a Service (DaaS) Team within Global Functions Technology, you will provide technical leadership and execution of development deliverables for the reimagined Finance Data Platform. The platform, leveraging public cloud infrastructure, will serve as the central repository of finance related datasets, with capabilities including the acquisition, standardization, enrichment, and provisioning, of positional/trade, sub‑ledger and general‑ledger trial balances, and reference data, and include capabilities supporting reconciliation, analytics, and reporting functions.

We are seeking a Data Engineer with extensive hands‑on experience in designing and developing data platforms. This role requires strong data architecture and engineering skills, effective written and verbal communication, a strong work ethic, and the ability to multi‑task effectively. Additionally, you must possess strong interpersonal, organisational, and problem‑solving skills, along with a demonstrated sense of urgency to respond to changing priorities.

What will you do?

This role will encompass an end‑to‑end system view from data sourcing, lineage, transformation, and storage standpoint to support complex advanced analytics and data management and governance needs and require extensive collaboration with Business architecture, System architecture, Business SME and Data Stewards.

• Work closely with the data team and other stakeholders to understand their data requirements and assist in building data solutions that cater to their needs.
• Design, develop, and support new and existing data pipelines, recommending improvements and modifications.
• Communicate strategies and processes around data modeling and architecture to cross‑functional groups.
• Identify, design, and implement internal process improvements.
• Utilise your expertise in data transformation techniques to enrich raw data, making it more accessible and valuable for analytics and reporting purposes.
• Build and implement ETL frameworks to improve code quality and reliability.
• Develop scripts and programs for converting various types of data into usable formats.
• Ensure the accuracy and consistency of data processing, results, and reporting.

What do you need to succeed?

Must Have

• Undergraduate degree/diploma in computer science/engineering or related technology discipline.
• 7+ years of experience in data engineering with at least 3 years of hands‑on experience in system integration, data engineering and cloud architecture, and tools & technologies listed below:
• Big‑Data/Lakehouse platforms as Cloudera Data Platform, Microsoft Azure, AWS
• Data transformation tools/technologies/platforms such as: Data Build Tool (DBT), Databricks, Snowflake.
• Orchestration: Apache Airflow/ Stonebranch UAC/Control‑M
• Cloud and Containers: OpenShift (OCP)/Docker/Kubernetes
• API Development: FastAPI, or other API framework
• Security: LDAP, Kerberos, OAuth 2.0, Microsoft Entra ID, HashiCorp Vault integration
• DevOps: GitHub Actions
• Programming languages: Python/Scala/Java
• Demonstrable experience with data management and governance practices.
• Demonstrable experience with SQL with any ANSI‑compliant RDBMS.
• Demonstrable experience with generative‑AI tools/technologies.

Nice to have

• Experience with/exposure to migrating data platforms from on‑premises to off‑premises (cloud) infrastructure.
• Experience with Capital Markets or other financial technology services’ middle/back‑office environments.
• Experience with/exposure to financial services’ products.

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.

#TECHPJ

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: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2026-04-29

Application Deadline: 2026-09-30

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.