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About the Role

As a Senior Manager, Engineering & Build (Hands-On Leader) within Global Functions Technology (GFT), you will lead an engineering team while contributing hands-on to design and deliver cloud-native, governed, and reliable data systems for the Anti-Money Laundering (AML) Data Foundation Hub.

Responsibilities

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.

Requirements

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.
Hands-on Snowflake expertise with Streams, Tasks, Snowpark, and Snowpipe.
Strong SQL and warehouse design skills.
Performance optimization experience.
Production experience with Spark (PySpark/Scala) for large-scale batch processing and optimization.
Strong data modeling (3NF/dimensional/data vault) and medallion architecture patterns (Bronze/Silver/Gold).
Experience with data quality frameworks, source-to-target reconciliation, lineage concepts and tooling, purge/retention strategies.
Experience with Airflow (or equivalent) for DAGs, SLAs, retries, and observability.
Experience with Git-based workflows and CI/CD for data (e.g., GitHub Actions/Jenkins).
Proficiency in dbt development, testing, documentation, and deployment.
Experience with containers, Kubernetes/OpenShift, Infrastructure-as-Code, and secure secret management.
Understanding of cost/performance trade-offs on cloud platforms.
Strong ownership, problem-solving, and communication skills.
Experience with incident management and postmortems.
Experience with Snowflake, Spark, dbt, Airflow, Python/Scala/Java, OpenShift/Kubernetes, and public cloud (e.g., AWS).
Experience with Kafka/CDC for near-real-time enrichment into batch layers (nice-to-have).
Experience with metrics, tracing, and logging practices and tooling across data pipelines (nice-to-have).
Experience with OAuth2/OIDC, data masking/tokenization, PII handling, and regulatory awareness in financial services/AML (nice-to-have).
Experience in financial services or other highly regulated industries (nice-to-have).
Cloud certifications (AWS) and familiarity with services such as Glue, EMR, EKS, SageMaker (nice-to-have).
Ability to influence and align diverse technical and non-technical partners (nice-to-have).
Hadoop ecosystem exposure (as legacy integration), where applicable (nice-to-have).

Skills

Snowflake
Spark
dbt
Airflow
Python
Scala
Java
OpenShift
Kubernetes
AWS
SQL
Data Modeling
Medallion Architecture
CI/CD
Infrastructure-as-Code
Data Quality
Source-to-Target Reconciliation
Lineage
Purge/Retention Strategies
Schema Evolution
SCD/CDC
Partitioning
Performance Tuning
Containerization
Secret Management
Incident Response
Postmortems
Ingestion Patterns
SLAs
Retries
Idempotency
Alerting
DQ Controls
Profiling
Constraints
dbt Tests
Application Development
Application Integrations
Application Maintenance
Applications Architecture
Big Data Management
Cloud Computing
Commercial Acumen
Data Warehousing (DW)
Distributed Computing
Enterprise Application Delivery
ETL Pipelines
Information Technology Management
Programming Languages
Snowflake Data Warehouse
Software Development Life Cycle (SDLC)
Software System Design
System Applications
Kafka
CDC
Observability
Metrics
Tracing
Logging
OAuth2/OIDC
Data Masking
Tokenization
PII Handling
Hadoop

Location

Toronto, Canada

Work Type

Full time

Experience Level

Senior Manager
10+ years in engineering
2-4+ years leading engineers

Benefits

Bonuses
Flexible benefits
Competitive compensation
Commissions
Stock where applicable
World-class training program in financial services
Flexible work/life balance options

About the Company

Global Functions Technology (GFT) partners across RBC to deliver transformative platforms and solutions.
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.