Senior Data Engineer

Sun Life

. Design and engineer data models for key business entities including Advisors, Clients, and Products .

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

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and engineering data models, ensuring data quality and integrity, and implementing data products for analytical use cases. Proficient in cloud technologies and programming languages essential for data processing and analytics.

Highest-signal resume keywords

AWSSnowflakePythonPySparkSQL

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ModelingETL PipelinesData QualityData GovernanceRelational Database SystemsAnalytical ModelsData IntegrationBig Data TechnologiesSpark OptimizationData Pipeline Logic

Soft Skills

Communication SkillsCollaborationStakeholder Engagement

Tools & Technologies

ParquetIcebergCloud Technologies

Certifications & Qualifications

Reliability Status Clearance

Industry Keywords

Data ManagementBusiness Data StrategyData ScienceMetadata Standardization

Tech Stack

Tools & technologies

AWSCloudETLPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and engineer data models for key business entities including Advisors, Clients, and Products
Maintain high data quality and integrity across data sources
Convert complex business and technical rules into data-flow and data-pipeline logic
Understand enterprise data and derive business value from it
Work with Data Science teams to implement data products for various use cases
Collaborate with stakeholders and incorporate requirements into solution designs
Standardize metadata into a common glossary and provide documentation 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 part of the Business Data Strategy

Requirements

What you’ll need

3–5 years 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 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
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
Experience with very large datasets and big data technologies
Excellent verbal and written communication skills
Ability to partner with Data Scientists and articulate insights from models and underlying data
Reliability Status Clearance required before starting employment
Ability to satisfactorily complete applicable background checks
Undergraduate degree in Computer Science, Mathematics, Engineering, or equivalent

Benefits

Comp & perks

Wellness programs supporting mental, physical, and financial health
Career paths with networking opportunities
Hybrid work flexibility from home and office
Accommodation available in the application process
Incentive plans for eligible employees, discretionary and based on individual and company performance