Lead Trolley’s data platform, pipelines, and data team. Power finance, fraud, reporting, and AI for the internet economy payouts platform.
About the role
- Senior Data Engineer building governed AWS and Snowflake data products for Sun Life’s Canadian insurance business. Partnering with analysts and data scientists to power enterprise analytics.
Responsibilities
- Design and engineer data models representing key business entities such as 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 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
- Bridge business-consumer requirements and data-engineering practitioners
- Partner with CXO business stakeholders, enterprise governance and risk partners, and CXO data practitioners
- Work with data analysts and data scientists to identify business opportunities, understand client behavior, and optimize sales cycles
Requirements
- 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 data governance
- 3+ years of experience and proficiency in Python, PySpark, and SQL
- Demonstrated 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
- Sound understanding of data management and data governance principles
- Proven ability to extract, conform, and integrate operational data sources into production-grade data products
- Experience with Parquet and Iceberg data formats
- Experience with very large datasets and big data technologies
- Excellent verbal and written communication skills and ability to partner with Data Scientists to articulate insights
- Understanding of AI and machine learning concepts and AWS/Snowflake AI services
- Knowledge of fundamental statistical models and techniques
- Knowledge and experience with DevOps technologies
- Experience in a large financial services organization
- Reliability Status Clearance required before employment
- Must satisfactorily complete applicable background checks before starting and during employment
- Undergraduate degree in Computer Science, Mathematics, Engineering, or equivalent
Benefits
- Wellness programs supporting mental, physical, and financial health
- Variety of career paths with networking potential
- Hybrid work flexibility between office and virtual work
- Incentive plans for eligible employees, subject to individual and company performance
- Accommodation support during the application process
- Employee well-being and mental health workplace initiatives
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