Data Platform Operations Engineer (London)

Overview

As a Data Platform Operations Engineer, you will safeguard the availability, performance, and scalability of the data platform while driving automation and site reliability improvements. You’ll collaborate with cross-functional teams to enforce governance, security, and data quality, and you’ll support data reconciliation and disaster recovery efforts. The role combines hands-on engineering with monitoring, deployment management, and on-call responsibilities to ensure SLAs are met. This is a chance to influence how data powers client-focused insights at RBC.

Pay / Benefits

• bonuses
• flexible benefits
• competitive compensation
• career development
• world-class training program
• coaching and leadership support

Responsibilities

• Maintain system reliability, uptime, and scale while delivering changes
• Collaborate with Data & Analytics, Security, and other teams to apply best practices
• Monitor performance, troubleshoot proactively, and document fixes
• Oversee deployments, data pipeline stability, and dashboard refreshes
• Implement security, governance, and data lifecycle management
• Keep documentation up to date and support disaster recovery planning
• Optimize the data quality platform and manage data governance processes
• Participate in on-call rotations for outside-hours support
• Design and maintain monitoring dashboards and SRE practices
• Automate operational processes and leverage AI to enhance efficiency and self-healing

Key requirements

• Experience supporting scalable, high-performance data platforms in hybrid Azure environments
• Hands-on SQL/ETL, CI/CD, DevOps, monitoring/logging, data security/governance (Purview, Collibra), and Git
• Familiarity with Agile methodologies and ITSM tools (ServiceNow, Jira)
• Incident management experience with high availability/disaster recovery
• Excellent communication and collaboration skills with ability to produce clear docs
• Engineering experience in Site Reliability Engineering (SRE) and ability to work under tight deadlines
• Databases & Tools: Microsoft SQL Server (administration, T-SQL, DML, DDL, SSIS), Databricks, Power BI
• Azure Technologies: ADLS, ADF, Azure SQL Database, Delta Lake, Azure DevOps, Logic Apps, Function Apps, Key Vaults, Storage Accounts
• Infrastructure & Automation: Terraform, Python/PySpark
• Expertise in data modeling, integration, ETL, governance, and security
• Nice-to-have: Datactics (or similar) and Generative/Agentic AI

• strong communication
• cross-team collaboration
• organization
• SQL
• ETL
• CI/CD

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