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Added 1 hour ago
Senior DevOps Engineer
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Full-time
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Senior Manager, Engineer & Build
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Senior Java Developer - Microservices, API, Python, ACBS, AFS/Commercial Lending
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Full-time
Strong expertise in Java and Python for back-end development.
Added 1 day ago
Senior Java Developer - Microservices, API, Python, ACBS, AFS/Commercial Lending
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Full-time
Strong expertise in Java and Python for back-end development.

RBC

Senior Manager, Engineer & Build

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 9, 2026
Posting language: English
Posted: Sep 25, 2026

Apply About employer

Applications open in a new tab.

Original job description

Job Description

Are you a hands-on data engineering leader who thrives on building high-performing teams and high-scale data platforms? 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 Data Foundation Hub to ingest enterprise data and power analytics and controls using a medallion architecture.

As a Senior Manager, Engineering & Build (Hands-On Leader), you will lead an engineering team while contributing ≈50% hands-on to design and deliver cloud-native, governed, and reliable data systems.

What will you do?

Lead, mentor, and grow a high-performing team; drive delivery excellence, coaching, goal setting, and continuous improvement.
Design and build batch and incremental pipelines across Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark, Snowpipes), Spark, and dbt.
Implement schema evolution, SCD/CDC, partitioning, and performance tuning.
Architect for reliability, scalability, and cost efficiency on cloud platforms.
Containerize jobs/services, run on Kubernetes/OpenShift, apply IaC, and secure secrets and credentials.
Own CI/CD for data (code review, environment promotion, data contract testing), versioned artifacts, and environment parity.
Partner with Platform/SRE on SLIs/SLOs, incident response, and postmortems.
Engineer resilient, observable ingestion patterns (batch first, with optional near-real-time).
Orchestrate with Airflow (or equivalent); enforce SLAs, retries, idempotency, and alerting.
Establish DQ controls (profiling, constraints, dbt tests), source-to-target reconciliation, and end-to-end lineage.
Implement purge/retention aligned to AML and regulatory requirements.

What do you need to succeed?

Must-have:

Experience depth: 10+ years in engineering delivering production pipelines and distributed systems at scale; 2–4+ years leading engineers with a proven balance of hands-on and people leadership.
Snowflake expertise: Hands-on with Streams, Tasks, Snowpark, and Snowpipe; strong SQL and warehouse design; performance optimization.
Distributed processing: Production experience with Spark (PySpark/Scala) for large-scale batch processing and optimization.
Modeling and architecture: Strong data modeling (3NF/dimensional/data vault) and medallion architecture patterns (Bronze/Silver/Gold).
Data governance controls: Data quality frameworks, source-to-target reconciliation, lineage concepts and tooling, purge/retention strategies.
Orchestration and automation: Airflow (or equivalent) for DAGs, SLAs, retries, and observability; Git-based workflows and CI/CD for data (e.g., GitHub Actions/Jenkins).
Dbt proficiency: Development, testing, documentation, and deployment of transformations with dbt.
Cloud-native and platform: Containers, Kubernetes/OpenShift, Infrastructure-as-Code, and secure secret management; understanding of cost/performance trade-offs.
Ways of working: Strong ownership, and excellent problem solving and communication; incident management and postmortems.
Technology focus: Snowflake, Spark, dbt, Airflow, Python/Scala/Java, OpenShift/Kubernetes, and public cloud (e.g., AWS).

Nice-to-have:

Streaming and events: Kafka/CDC for near-real-time enrichment into batch layers.
Observability: Metrics, tracing, and logging practices and tooling across data pipelines.
Security and privacy: OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services/AML.
Regulated domains: Experience in financial services or other highly regulated industries.
Cloud depth: Certifications (AWS) and familiarity with services such as Glue, EMR, EKS, SageMaker.
Stakeholder management: Ability to influence and align diverse technical and non-technical partners.
Hadoop ecosystem exposure (as legacy integration), where applicable.

What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

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
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 take on progressively greater accountabilities
Access to a variety of job opportunities across business and geographies

Job Skills

Application Development, Application Integrations, Application Maintenance, Applications Architecture, Commercial Acumen, Enterprise Application Delivery, Information Technology Management, Programming Languages, Software Development Life Cycle (SDLC), System Applications

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:

2026-09-25

Application Deadline:

2026-10-09

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 and mentor a high-performing data engineering team while contributing hands-on to the design and delivery of cloud-native data systems. Oversee the development of batch and incremental pipelines, ensuring reliability, scalability, and adherence to data governance and quality standards.

Requirements

Requires over 10 years of experience in engineering production pipelines and distributed systems, with at least 2-4 years of leadership experience. Must possess deep expertise in Snowflake, Spark, dbt, and cloud-native orchestration tools within a regulated environment.

Skills

Data engineering
Snowflake
Spark
Dbt
Kubernetes
OpenShift
Airflow
Python
Scala
Java
Data modeling
CI/CD
Infrastructure-as-code
Cloud platforms
Leadership
Data governance

Benefits

Bonuses
Flexible benefits
Competitive compensation
Stock options
Training program
Flexible work/life balance

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Snowflake
Spark
Dbt
Airflow
Kubernetes
OpenShift
Python
Scala
Java
AWS
CI/CD
Infrastructure-as-Code
Data Modeling
Medallion Architecture
Data Governance
Anti-Money Laundering
Financial Services
Distributed Systems
Cloud-native
SCD/CDC
Data Quality
Observability
Git
Jenkins
GitHub Actions
SLA
SLO
Data Vault
3NF

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