Job Title: Sr. IFRS17 Data Engineer
Job Type: Full Time
Location: Toronto, ON (Onsite 4 Days)
Job Description
We are seeking a highly experienced Sr. IFRS17 Data Engineer with strong expertise in IFRS 17, data analysis, and the insurance domain. The ideal candidate will have advanced skills in Python, PySpark, SQL, and data engineering, with experience designing scalable backend systems and ETL pipelines.
The candidate will provide technical leadership, guide engineering teams, and ensure high performance, scalability, and reliability of data solutions while collaborating with cross-functional teams.
Key Responsibilities
Develop and maintain backend systems using Python and PySpark.
Design, implement, and optimize data engineering and ETL pipelines.
Analyze complex datasets and support IFRS 17 reporting and insurance data requirements.
Lead technical architecture, design, and implementation of software systems.
Collaborate with product owners and stakeholders to define and prioritize requirements.
Mentor engineers, provide technical guidance, and conduct code reviews.
Develop and maintain architecture diagrams, technical specifications, and documentation.
Collaborate with DevOps and Operations teams to ensure smooth deployment and system reliability.
Implement and support DevOps practices and CI/CD pipelines.
Troubleshoot complex technical issues and recommend effective solutions.
Research and evaluate new technologies to improve existing systems and processes.
Required Skills
Robust knowledge of IFRS 17 and the insurance domain.
Expertise in data analysis and SQL.
Advanced programming skills in Python and PySpark.
Experience developing scalable data engineering solutions and ETL pipelines.
Strong understanding of software architecture and system design.
Experience with DevOps practices and CI/CD pipelines.
Excellent technical leadership, mentoring, and problem-solving skills.
Strong communication and cross-functional collaboration abilities.
Good to Have
Exposure to Dataiku.
Knowledge of modern data engineering technologies and frameworks.
Experience improving data processing performance and operational efficiency.