Rbc

Staff,DataEngineer(GlobalSecurity)

Toronto, Ontario, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Staff, Data Engineer (Global Security) at Rbc. Skills: Snowflake Expertise, Data Pipeline Development, ETL/ELT, Python, Airflow, Data Governance. Build and Optimize Data Pipelines. Design, develop, and enhance scalable ETL/ELT pipelines to migrate, transform, and load large datasets from diverse sources”

What You'll Achieve.

Deliver trusted advice to help our clients thrive and communities prosper; Achieving success that is mutual; Ability to make a difference and lasting impact; Create value for our clients and communities

Industry & Context.

Problems you'll solve

Troubleshoot issues; Group Problem Solving; Critical Thinking; Problem Solving

What They're Looking For.

Must Have

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, 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 Have

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

What You'll Do.

Build and Optimize Data Pipelines

and enhance scalable ETL/ELT pipelines to migrate

and load large datasets from diverse sources

Ensure seamless integration for analytics

Drive Technical Innovation

and efficient technical solutions

Champion Snowflake Best Practices

Guide users on effective Snowflake utilization

Establish standards for data consumption

and workflow integration

Design and implement high-impact stored procedures

Collaborate Across Teams

Translate data requirements into robust solutions

Strengthen Data Governance

Implement and maintain best practices for metadata management

Ensure Performance and Scalability

Monitor system performance

Optimize queries/processes

Automate and Streamline Workflows

Use Python scripting and orchestration tools (e.g.

Airflow) to automate platform utilities and workflows

Document and Share Knowledge

Create clear technical documentation for processes

How You'll Work.

Team & Collaboration

Partner with cross-functional stakeholders; Collaborate Across Teams; Guide users/teams on platform best practices; Present technical solutions in cross-functional meetings; Foster team collaboration; Work in a dynamic, collaborative, progressive and high-performing team; Collaboration; Working together as One RBC; Effectively collaborate

Communication Scope

Present technical solutions in cross-functional meetings; Share Knowledge; Communication

Full Job Description

**_Job Description_** WHAT WILL YOU DO? ​ * **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. WHAT DO YOU NEED TO SUCCEED? * **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 larg

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