Senior Data Engineer

Sun Life

. Design and engineer data models for Advisor, Client, and Product business entities .

Posted 10/23/2026full-timeToronto • CanadaSenior💰 CA$85,000 - CA$128,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and engineering data models, maintaining data quality, and implementing data products for analytical use cases. Proficient in cloud technologies, data governance, and collaboration with stakeholders to derive business value from data.

Highest-signal resume keywords

AWSSnowflakePythonPySparkSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingETL PipelinesData QualityData GovernanceData IntegrationRelational Database SystemsAnalytical ModelsBig Data TechnologiesData ManagementPerformance Optimization

Soft Skills

Strong Communication SkillsCollaborationStakeholder Engagement

Tools & Technologies

ParquetIcebergAgileDevOps

Certifications & Qualifications

Reliability Status Clearance

Industry Keywords

Financial ServicesData ScienceData ProductsBusiness Intelligence

Tech Stack

Tools & technologies

AWSCloudETLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and engineer data models for Advisor, Client, and Product business entities
Maintain data quality and integrity across data sources
Convert business and technical rules into data-flow and data-pipeline logic
Understand enterprise data and interpret it to derive business value
Work with Data Science teams to implement data products for varied use cases
Collaborate with stakeholders and incorporate requirements into solution designs
Standardize metadata into a common glossary and document it for data consumers
Build enriched data products supporting analytical models across Canadian business units
Partner with CXO stakeholders, enterprise governance and risk partners, and data practitioners
Bridge business-consumer requirements and data-engineering practices as a senior individual contributor

Requirements

What you’ll need

3–5 years of hands-on experience with major cloud technologies and programming languages for data processing and analytics
3+ years of experience with AWS and Snowflake for ETL pipelines, catalog management, data quality, and governance
3+ years of experience and proficiency in Python, PySpark, and SQL
Experience optimizing Spark and SQL job cost and performance
5 years of hands-on experience with relational database systems, relational, dimensional, and analytical models
3–5 years of experience engineering data products for analytical models
3–5 years building feedback loops between model deployment and data products
Sound understanding of data management and data governance principles
Ability to extract, conform, and integrate operational data sources into production-grade data products
Experience with Parquet and Iceberg data formats
Experience with large datasets and big data technologies
Strong verbal and written communication skills and ability to partner with Data Scientists
Reliability Status Clearance required before starting employment
Ability to satisfactorily complete applicable background checks
Undergraduate degree in Computer Science, Mathematics, Engineering, or equivalent
Understanding of Agile operating models, AI and machine learning concepts, AWS and Snowflake AI services, statistical models, and DevOps technologies is an asset
Experience in a large financial services organization is an asset

Benefits

Comp & perks

Wellness programs supporting mental, physical, and financial health
Variety of career paths and networking opportunities
Hybrid work flexibility between home and office
Incentive plans for eligible employees, subject to individual and company performance
Disability accommodations in the application process