Staff, Data Engineer (Global Security)

Royal Bank of Canada • Toronto, ON

3d • Onsite

About The Position

This role focuses on building and optimizing data pipelines within Global Security. The Data Engineer will be responsible for designing, developing, and enhancing scalable ETL/ELT pipelines to migrate, transform, and load large datasets from diverse sources. The position involves leveraging advanced tools and techniques for reusable, secure, and efficient technical solutions, including data sharing and governance. A key aspect of the role is championing Snowflake best practices, guiding users on effective utilization, and establishing standards for data consumption, storage, and workflow integration. The Data Engineer will also collaborate with cross-functional stakeholders to translate data requirements into robust solutions for analytics, reporting, AI, and machine learning initiatives. Strengthening data governance through best practices for metadata management, access controls, and compliance is crucial. The role also includes ensuring performance and scalability by monitoring systems, troubleshooting issues, and optimizing processes, as well as automating and streamlining workflows using Python and orchestration tools like Airflow. Documenting processes, architectures, and data models is also a key responsibility.

Requirements

• Snowflake Expertise: Hands-on experience with Snowflake (e.g., designing stored procedures, optimizing queries, data storage/consumption best practices).
• Data Pipeline Development: Proficiency in building, optimizing, and maintaining ETL/ELT pipelines for large-scale data migration and transformation.
• Programming & Automation: Strong scripting skills in Python for automation and tool development. Experience with workflow orchestration tools (e.g., Airflow).
• Data Governance & Security: Knowledge of implementing data governance practices (metadata management, access controls, compliance).
• Performance Optimization: Skills in monitoring, troubleshooting, and optimizing database/query performance for scalability.

Nice To Haves

• Technical Collaboration & Communication: Ability to guide users/teams on platform best practices and present technical solutions in cross-functional meetings.
• DevOps & CI/CD Practices: Knowledge of version control (Git), containerization (Docker), or CI/CD pipelines for data engineering workflows.
• Documentation & Knowledge Sharing: Experience documenting technical processes, architectures, and data models for team use.
• Advanced Data Modeling: Experience designing dimensional models (e.g., star/snowflake schemas) or optimizing data warehouses for analytics.

Responsibilities

• Build and Optimize Data Pipelines: Design, develop, and enhance scalable ETL/ELT pipelines to migrate, transform, and load large datasets from diverse sources (e.g., databases, APIs, flat files), ensuring seamless integration for analytics, reporting, and AI solutions.
• Drive Technical Innovation: Leverage advanced tools and techniques to create reusable, secure, and efficient technical solutions that align with business needs and project lifecycle deliverables, including data sharing and governance.
• Champion Snowflake Best Practices: Guide users on effective Snowflake utilization, establishing standards for data consumption, storage, and workflow integration while designing and implementing high-impact stored procedures.
• Collaborate Across Teams: Partner with cross-functional stakeholders to translate data requirements into robust solutions that empower analytics, reporting, AI, and machine learning initiatives.
• Strengthen Data Governance: Implement and maintain best practices for metadata management, access controls, and compliance to ensure data integrity and security.
• Ensure Performance and Scalability: Monitor system performance, troubleshoot issues, and optimize queries/processes to maximize efficiency and scalability.
• Automate and Streamline Workflows: Use Python scripting and orchestration tools (e.g., Airflow) to automate platform utilities and workflows, reducing manual effort and enhancing reliability.
• Document and Share Knowledge: Create clear technical documentation for processes, architectures, and data models to foster team collaboration and institutional knowledge.

Benefits

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable.
• Leaders who support your development through coaching and managing opportunities.
• Ability to make a difference and lasting impact.
• Work in a dynamic, collaborative, progressive, and high-performing team.
• A world-class training program in financial services.
• Opportunities to do challenging work.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed