Lead Data Engineer

JobCubby; Mather (CA); On-site; USD 86,000 - 129,000; Full time

Job summary

RBC in Toronto is seeking a Lead Data Platform Engineer to own the design and build of an AWS-based data platform for AML analytics and controls. You will mentor engineers, drive technical direction, and deliver cloud-native data solutions across Bronze/Silver/Gold layers using Snowflake, Spark, and dbt.

You will lead platform ownership, establish secure baselines, and implement CI/CD for data pipelines while ensuring observability, reliability, and cost efficiency across S3, Glue, EMR, and EKS.

Qualifications

• 7+ years delivering production data pipelines and distributed systems on cloud platforms.
• AWS platform depth with S3, Glue, EMR, EKS, and RDS; IaC and security baselines.
• Snowflake expertise with Streams, Tasks, Snowpark; strong SQL and warehouse design.
• Distributed processing with Spark for large-scale batch processing; medallion architecture knowledge.
• Orchestration with Airflow or equivalent; CI/CD for data pipelines.
• Reliability and security design including HA/DR, encryption, and least-privilege policies.

Responsibilities

• Technical leadership and platform ownership for AML Data Foundation Hub on AWS.
• Mentor engineers through design reviews, pair programming, and standards.
• Build secure, scalable data platforms using AWS services and Snowflake.
• Design and implement Bronze/Silver/Gold data pipelines with Spark, Snowflake, and dbt.
• Implement schema evolution, SCD/CDC, and performance tuning across compute and storage.
• Own CI/CD for data components and ensure observability and SLAs.
• Collaborate with Platform/SRE on SLI/SLOs, capacity planning, and standardization.

Skills

Technical leadership

Cloud data architecture

AWS data platform

S3/Glue/EMR/EKS/RDS

Snowflake

Spark

dbt

Airflow

IaC (CloudFormation/Terraform)

Data governance & security

CI/CD for data pipelines

Incident response & postmortems

Tools

Snowflake

Airflow

dbt

Terraform

CloudFormation

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 SLI/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?

• 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

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: 2026-08-31

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Job Skills

Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements Analysis

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.