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RBC

Lead Data Engineer

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Oct 31, 2026
Posting language: English
Posted: Oct 5, 2026

Original job description

Job Description

What is the opportunity?

Are you a hands-on data platform engineer who thrives on building cloud-native, high-scale data platforms and enabling teams on top of them? Come join us!

Global Functions Technology (GFT) partners across RBC to deliver transformative platforms and solutions. In Anti-Money Laundering (AML), we are building a new Data Foundation Hub to ingest enterprise data and power analytics and controls using a medallion architecture. As a Lead Data Platform Engineer, you will be a senior individual contributor and technical lead, owning the design and build of our AWS-based data platform and mentoring other engineers.

You will work 70–80% hands-on across AWS (EKS, S3, RDS, EMR, Glue, Airflow), Snowflake, Spark, and dbt to deliver cloud-native, governed, and reliable data systems.

What will you do?

Technical leadership and platform ownership
- Lead the technical direction for the AML Data Foundation Hub on AWS.
- Mentor and coach engineers (tech design reviews, pair programming, standards), influencing quality and delivery.
Cloud-native data platform on AWS (hands-on)
- Design and build secure, scalable data platforms using AWS S3, Glue, EMR, RDS, and EKS.
- Define patterns for data lake and warehouse integration (e.g., S3 + Snowflake) including partitioning, storage classes, encryption, and cost optimization.
- Implement Infrastructure-as-Code (e.g., CloudFormation/Terraform) for repeatable environments, networking, IAM roles/policies, and security baselines.
Data engineering and architecture (medallion)
- Design and build batch and incremental pipelines across Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark), Spark on EMR, and dbt.
- Implement schema evolution, SCD/CDC, partitioning, and performance tuning across both compute and storage (S3, EMR, Snowflake, RDS).
Ingestion, orchestration, and observability
- Engineer resilient, observable ingestion patterns into S3/Snowflake/RDS.
- Orchestrate pipelines using Airflow (or equivalent) and/or AWS-native services (e.g., event triggers), enforcing SLAs, retries, idempotency, and alerting.
- Build operational dashboards and alerts for pipeline health, platform capacity, and cost.
Reliability, DR, and security
- Design for high availability, resiliency, and disaster recovery (multi-AZ,/region backup/restore, RPO/RTO-aware architectures).
- Implement secrets management, encryption, IAM least-privilege, and network security in partnership with Security and Platform/SRE.
- Participate in incident response and postmortems; drive root-cause fixes and hardening of the platform.
DevOps for data and platform enablement
- Own CI/CD for data and platform components: code review, environment promotion, automated tests (unit, integration, data contract), and versioned artifacts.
- Partner with Platform/SRE on SLIs/SLOs, capacity planning, and platform standardization across squads.
Cross-functional collaboration
- Translate AML business and control objectives into technical roadmaps, platform capabilities, and reusable patterns.

What do you need to succeed?

Must-have

Experience depth: 7+ years delivering production data pipelines and distributed systems at scale on cloud platforms; demonstrated ability to operate as a senior IC and technical lead influencing architecture and quality across a team.
AWS platform depth: Hands-on with S3, Glue, EMR, EKS, and RDS; proficiency with IaC (CloudFormation or Terraform), IAM least-privilege design, VPC/networking, and security baselines.
Snowflake expertise: Hands-on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization across compute and storage.
Distributed processing: Production experience with Spark (PySpark/Scala) for large-scale batch processing, optimization, and tuning.
Data engineering and architecture: Medallion architecture patterns (Bronze/Silver/Gold), schema evolution, SCD/CDC, partitioning, and end-to-end pipeline performance tuning.
Orchestration and automation: Airflow (or equivalent) for DAGs, SLAs, retries, idempotency, and observability; Git-based workflows and CI/CD for data pipelines (e.g., GitHub Actions/Jenkins).
Reliability and security: Designing for HA/DR (multi-AZ, backup/restore, RPO/RTO); encryption, secrets management, and network security in partnership with Platform/SRE.
DevOps for data: Ownership of automated testing (unit, integration, data contract), environment promotion, and versioned artifacts.
Ways of working: Strong ownership, structured problem-solving, and clear technical communication; experience with incident response and postmortems.

Nice-to-have

dbt proficiency: Development, testing, documentation, and deployment of transformations with dbt.
Observability: Metrics, tracing, and logging practices across data pipelines and platform components.
Security and privacy: OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services or AML.
Regulated domains: Prior experience in financial services or other highly regulated industries.
Cloud depth: AWS certifications (e.g., Solutions Architect, Data Engineer) and hands-on familiarity with SageMaker or additional AWS-native data services.
Data governance: DQ frameworks, source-to-target reconciliation, lineage tooling, and purge/retention strategies.
Hadoop ecosystem: Exposure to legacy Hadoop stack where relevant to integration patterns.

What's in it for you?

As a team, we thrive on the challenge to be our best, encourage progressive thinking for continued growth, and collaborate with one another to deliver trusted advice to help our clients thrive and our communities prosper. We respect and care about all of our team members and support one another in reaching our fullest potential. We work together to make a difference in our communities and to achieve success that is mutual.

This opportunity will provide you with:

Work in a dynamic, collaborative, progressive, and high-performing team
Opportunities to do challenging work, make a difference and lasting impact
Continuous learning and flexibility to work on projects that you are passionate about
Leaders who support your development through coaching and managing opportunities

#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:

2026-08-06

Application Deadline:

2026-10-31

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.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

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More about this job

Responsibilities

Lead the technical design and development of a cloud-native data platform on AWS using a medallion architecture. Mentor engineering team members while ensuring the reliability, security, and scalability of data pipelines and infrastructure.

Requirements

Requires 7+ years of experience in data engineering and distributed systems on cloud platforms, specifically AWS. Proficiency in Snowflake, Spark, orchestration tools like Airflow, and Infrastructure-as-Code is essential for this senior role.

Skills

AWS
Data Engineering
Snowflake
Spark
dbt
Airflow
Infrastructure-as-Code
Terraform
CloudFormation
EKS
Python
Scala
SQL
Data Architecture
CI/CD
Distributed Systems

Benefits

Continuous learning
Professional development coaching
Collaborative work environment

Visa sponsorship

Not detected in the job text

Keywords

AWS
Data Engineering
Snowflake
Spark
dbt
Airflow
EKS
S3
Glue
RDS
Medallion Architecture
Infrastructure-as-Code
Terraform
CloudFormation
CI/CD
Distributed Systems
PySpark
Scala
SQL
Data Lake
Data Warehouse
IAM
VPC
SRE
DevOps
Disaster Recovery
Data Governance
Anti-Money Laundering
Financial Services
Cloud-native

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