Data Engineer – IBM Information Analyzer, Ataccama, Python & SQL
Summary
Data Engineer on RBC's Metadata Engineering team designing data architectures, pipelines, and data-quality solutions using IBM Information Analyzer, Ataccama, Python, and SQL in a hybrid Toronto setup (4 days onsite). Focuses on DevOps/CI/CD, secure coding practices, and exploring AI/ML enhancements for the data platform.
Data Engineer – IBM Information Analyzer, Ataccama, Python & SQL
Toronto, ON - Hybrid (4 Days WFO)
Job Description
What is the Opportunity?
The Metadata Engineering team is undertaking multiple complex enterprise-wide initiatives as part of RBCs ongoing plan to improve data management and data-driven decision-making across the organization. In this role you will be responsible for strategically planning and managing successful implementation of data architectures and engineering solutions. The role will coordinate, develop, lead, communicate and execute activities to ensure objectives are accomplished on time.
What Will You Do?
• Design, develop, test, and deploy complex data architectures and reusable data assets that enable analytics and reporting capabilities across the organization
• Build and maintain data pipelines with strong attention to code quality, security standards, automated testing, and comprehensive documentation
• Support deployment pipelines and DevOps practices to ensure reliable data platform operations and system stability
• Implement monitoring, logging, and alerting solutions to maintain visibility into data pipeline health and proactively identify performance issues
• Identify and remediate security vulnerabilities in data systems and code; conduct peer code reviews with focus on secure coding standards and best practices
• Explore and evaluate emerging technologies and AI/ML techniques to enhance data engineering capabilities and identify opportunities for process optimization
• Collaborate with business and technology teams to understand requirements and design data solutions aligned with organizational strategy and compliance standards
• Independently resolve complex data engineering problems by identifying areas for improvement and implementing scalable solutions
What Do You Need to Succeed?
Must Have:
• Hands on experience on Data Quality Tools IBM Information Analyzer and Ataccama
• Migration experience with Data Quality tools to migrate rules to target systems
• 3-5 years of data engineering experience with proven expertise in designing and deploying data architectures
• Strong Python and SQL skills for data pipeline development, querying, and optimization
• Experience with DevOps practices including CI/CD pipelines, infrastructure automation, and deployment processes
• Security-focused mindset with understanding of secure coding standards and vulnerability management
• Strong code quality discipline with experience in testing frameworks, code reviews, and quality standards
Nice to Have:
• Experience with Java or other object-oriented scripting languages
• Hands-on experience with Snowflake or other cloud data platforms
• Familiarity with agentic AI systems and AI/ML model integration into data pipelines
• Experience with AI/ML model integration and data science workflows