Lead Data Engineer

Job Description

What is the opportunity?

RBC Insurance, through its operating entities, provides a wide range of travel, life, health, home, auto, wealth and insurance products and solutions. Also, it offers creditor and business reinsurance services to both individual and group clients. We are one of the largest insurance companies within a Canadian bank and among the fastest growing insurance organizations in the country. RBC Insurance employs more than 3,200 employees around the globe, and is the brand name for the insurance operating entities of Royal Bank of Canada.

What will you do?

1. Production-Ready Data Pipeline Development

• Design, build, and deploy enterprise-grade data pipelines that operate reliably in production environments

• Implement comprehensive testing, monitoring, and alerting systems to ensure 24/7 data availability

• Take end-to-end ownership of data solutions from conception through production deployment and ongoing maintenance

• Establish robust CI/CD practices for data engineering workflows

2. Cloud Data Architecture & Migration

• Lead cloud data migration initiatives, transitioning legacy systems to modern cloud platforms

• Architect scalable, secure, and cost-effective cloud-based data infrastructure

• Optimize data storage, processing, and retrieval performance across distributed systems

• Implement disaster recovery and business continuity plans for critical data assets

3. Advanced Data Engineering & Transformation

• Build and maintain sophisticated ETL/ELT pipelines processing high-volume structured and unstructured data

• Develop optimized SQL queries, stored procedures, and automation scripts for complex data transformations

• Ensure data quality, lineage, and governance standards throughout all data processes

• Collaborate with cross-functional teams to implement scalable data models and architectures

4. API Development & Integration

• Design and develop high-performance RESTful APIs and Graph
  
  QL endpoints for data access and integration

• Build secure, scalable API gateways that enable seamless data consumption across enterprise applications

• Implement API versioning, documentation, and monitoring strategies for production environments

• Integrate with third-party APIs and microservices to create comprehensive data ecosystems

5. Analytics Enablement & BI Integration

• Engineer data solutions that power real-time and batch analytics across the organization

• Optimize data structures and pipelines for seamless integration with Tableau and other BI platforms

• Enable self-service analytics capabilities through well-designed data marts and APIs

• Support advanced analytics and machine learning initiatives through feature engineering

6. Performance Engineering & Innovation

• Proactively identify and resolve performance bottlenecks in production data systems

• Implement comprehensive observability solutions including logging, monitoring, and alerting

• Drive continuous improvement initiatives to enhance system reliability and efficiency

• Research and implement emerging technologies to maintain competitive advantage

7. Technical Leadership & Collaboration

• Provide technical mentorship and establish data engineering best practices across teams

• Partner with Data Scientists, Analysts, and Business stakeholders to translate requirements into technical solutions

• Ensure compliance with enterprise security, privacy, and regulatory frameworks

• Drive innovation through proof-of-concepts and technical experimentation

What do you need to succeed?

Must-have

5+ years of Professional Experience with the following:

• Production Experience
  :
  Proven track record of delivering and maintaining data solutions in enterprise production environments

• Self-Driven Mindset
  :
  Demonstrated ability to work independently, take ownership, and drive projects to completion with minimal supervision

• Technical Expertise
  :
  Advanced proficiency in SQL, Python, and modern cloud-based data engineering frameworks

• Cloud Mastery
  :
  Hands-on experience with AWS, Azure, or Google Cloud Platform including native data services

• Data Platform Experience
  :
  Deep knowledge of Snowflake, Big Query, Redshift, or similar enterprise data warehouses

• ETL/ELT Proficiency
  :
  Extensive experience with Apache Airflow, DBT,…