Lead Data Engineer
Confirmed on the employer's own hiring board on Sep 25, 2026. First seen by Alion on Sep 16, 2026.
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 directionfor the AML Data Foundation Hub on AWS.
Mentor and coachengineers (techdesign reviews, pair programming, standards), influencing quality and delivery.
Cloud-native data platform on AWS (hands-on)
Design and build secure, scalable dataplatforms using AWS S3, Glue, EMR, RDS, and EKS.
Define patterns for data lake and warehouseintegration (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 pipelinesacross Bronze/Silver/Gold layers using Snowflake (Streams, Tasks, Snowpark),Spark on EMR, and dbt.
Implement schema evolution, SCD/CDC, partitioning, and performance tuning across bothcompute and storage (S3, EMR, Snowflake, RDS).
Ingestion, orchestration, and observability
Engineer resilient, observable ingestion patterns intoS3/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 dashboardsand alerts for pipeline health, platform capacity, and cost.
Reliability, DR, and security
Design for high availability, resiliency, and disaster recovery (multi-AZ,/regionbackup/restore, RPO/RTO-aware architectures).
Implement secrets management, encryption, IAM least-privilege, and network security inpartnership with Security and Platform/SRE.
Participate in incident response and postmortems; drive root-cause fixes and hardening ofthe platform.
DevOps for data and platform enablement
Own CI/CD for data andplatform 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
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Job Skills
Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements AnalysisAdditional Job Details
Address:
RBC CENTRE, 155 WELLINGTON ST W:TORONTOCity:
TorontoCountry:
CanadaWork hours/week:
37.5Employment Type:
Full timePlatform:
TECHNOLOGY AND OPERATIONSJob Type:
RegularPay Type:
SalariedPosted Date:
2026-08-06Application Deadline:
2026-09-30Note: 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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