Senior Data Engineer

CI Financial•Toronto, ON

8d•Onsite

About The Position

At CI, we see a great place to work as one that is a safe place for everyone to have a voice, where people are empowered to take ownership over meaningful work, where there is an opportunity to grow through stretching themselves, where they can work on innovative products and projects, and where employees are supported and engaged in doing so. We are currently seeking a Senior Data Engineer to join the Data, AI & Analytics (DNA) Team. A successful data engineering candidate will demonstrates a deep understanding of database concepts, data pipeline design, while also having the ability to communicate complex ideas clearly, and have experience in implementing scalable solutions that have positively impacted business outcomes.

Requirements

8+ years of hands‑on experience in data engineering, building and operating scalable ELT/ETL pipelines and data integration solutions.
4+ years of experience with data warehousing and Snowflake.
Strong SQL expertise and solid experience with dbt, including model design and testing
Experience with CI/CD pipelines for data platforms, including source control, automated testing, and deployments (e.g., Bitbucket, Jenkins, Git-based workflows).
Strong understanding of data architecture and data modeling
Ability to diagnose and solve complex, open‑ended problems and deliver production‑ready solutions.
Experience supporting production data platforms, including troubleshooting performance, and pipeline reliability issues.

Nice To Haves

Experience with Data Vault 2.0 is an asset.
Experience in the Financial Services Industry is an asset.

Responsibilities

Design, build, and optimize highly scalable, reliable data pipelines to support ELT/ETL to/from diverse source systems and platforms.
Develop reusable frameworks and automation to standardize data ingestion, transformations, reconciliations, testing, and monitoring.
Perform thorough code reviews to ensure solutions meet performance, scalability, security, and maintainability standards.
Define, document, and enforce data engineering standards for the platform.
Partner closely with business & analytics stakeholders to translate requirements into scalable technical solutions.
Maintain and improve the CI/CD pipeline for data platforms, including source control, build, test, and deployment workflows (e.g., Bitbucket, Jenkins, automated testing).
Troubleshoot and resolve production issues such as data quality defects, pipeline failures, performance bottlenecks, and dependency breaks.
Proactively identify opportunities to optimize and harden existing pipelines for reliability, observability, and operational efficiency.