What is the Opportunity?
RBC Capital Markets (RBC CM) is looking for a technical specialist responsible for documenting, validating, and maintaining end-to-end data lineage across Capital Markets technology ecosystem. This role goes beyond business-level data mapping to trace actual data flows across systems, tools, and platforms. The specialist will work closely with the Data Governance and Enterprise Data teams to identify control gaps, ensure data quality, and support enterprise data compliance initiatives.
What will you do?
- Build and maintain technical data lineage mappings that trace data flows across Capital Markets systems (e.g., OMS → Kafka/Event Streams → Data Lake architectures)
- Document and validate comprehensive data lineage across Capital Markets systems and infrastructure using Collibra Data Intelligence Platform and Informatica Enterprise Data Catalog
- Map data flows from source systems through transformation layers to end-user applications and reporting systems
- Read and interpret ETL jobs, stored procedures, and data pipelines to understand actual data movement and transformation
- Identify control gaps in data pipelines and recommend remediation strategies to strengthen data governance and reduce operational risk
- Collaborate with technology teams, data engineers, and business stakeholders to validate lineage accuracy
- Ensure alignment between documented flows and actual system behavior
- Support compliance reporting and audit requirements related to data provenance and data quality
- Own and drive regulatory data analysis work independently, managing field-level mapping projects from initiation through resolution
What do you need to succeed?
Must Have:
- Bachelor's degree in Computer Science, Information Technology, Data Science, or related field, or equivalent professional experience in data engineering or enterprise data architecture
- 5+ years of experience in data engineering, data governance, or enterprise data architecture roles
- Experience leading enterprise level program management initiatives
- Demonstrated experience building and maintaining data lineage in large, complex data environments
- Experience working with data warehouse arc