Senior IFRS 17 Data Engineer / Toronto, ON - (Onsite) FTE

Job Title: Senior IFRS 17 Data Engineer

Location: Toronto, ON

Work Model: Onsite – 4 Days per Week

Role Overview

We are seeking an experienced Senior IFRS 17 Data Engineer with strong expertise in insurance data, IFRS 17, data analysis, SQL, Python, and PySpark. The ideal candidate will be responsible for designing, developing, and maintaining scalable data engineering solutions and ETL pipelines that support IFRS 17 reporting and insurance data processing.

This role requires a hands-on technical leader who can drive solution architecture, guide engineering teams, improve data processing performance, and collaborate with business, product, DevOps, and operations teams to deliver reliable, high-quality data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions using Python, PySpark, and SQL.
• Build, optimize, and support ETL/ELT pipelines for large-scale insurance data processing and IFRS 17 reporting.
• Apply strong knowledge of IFRS 17 accounting standards, insurance business processes, and insurance data structures to develop effective data solutions.
• Perform complex data analysis, data transformation, validation, reconciliation, and quality checks.
• Lead technical architecture, solution design, implementation, and performance optimization.
• Collaborate with business stakeholders and product owners to gather requirements, define priorities, and translate business needs into technical solutions.
• Provide technical leadership, mentoring, coaching, and code reviews for engineering team members.
• Establish coding standards, engineering best practices, and quality controls.
• Develop and maintain technical documentation, including architecture diagrams, data flows, technical specifications, and implementation guidelines.
• Collaborate with DevOps and Operations teams to support deployments, production operations, troubleshooting, and issue resolution.
• Implement and maintain CI/CD pipelines and DevOps practices to improve delivery efficiency and system reliability.
• Research emerging technologies, evaluate frameworks, and recommend improvements to data engineering architecture and processes.

Must-Have Skills

• IFRS 17 & Insurance Domain: Demonstrated knowledge of IFRS 17, insurance data, and insurance business processes.
• Data Engineering: Strong experience designing and implementing scalable ETL/ELT pipelines.
• Python: Advanced programming skills for backend development and data processing.
• PySpark: Hands-on expertise in distributed data processing, transformation, and performance optimization.
• SQL & Data Analysis: Strong SQL skills, complex data analysis, data validation, and troubleshooting.
• Technical Leadership: Experience leading technical design, architecture, implementation, mentoring, and code reviews.
• DevOps & CI/CD: Experience with automated build, testing, deployment, and release processes.
• Communication & Collaboration: Ability to work effectively with business stakeholders, product owners, engineering teams, and operations.

Good-to-Have Skills

• Exposure to Dataiku for data preparation, analytics, or data pipeline development.
• Experience improving data engineering frameworks, processes, and operational efficiency.
• Familiarity with enterprise data platforms and modern data engineering practices.

Required Qualifications

• Significant hands-on experience in data engineering and backend development.
• Demonstrated expertise in Python, PySpark, SQL, and data analysis.
• Practical knowledge of IFRS 17 and the insurance industry.
• Proven ability to lead technical initiatives, make architectural decisions, and mentor engineers.
• Strong analytical, problem-solving, debugging, and communication skills.
• Ability to adapt to evolving business requirements and new technologies.