Data Engineer

CI Financial•Toronto, ON

44d•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 Data Engineer to join the Data and Analytics team in the Wealth Technology group at CI Wealth. The Data and Analytics team supports the organization through data management, data governance, reporting, and business intelligence and insights. The successful candidate will work on data pipeline and data transformation tasks that underly these strategic pillars. The ideal candidate will have a strong background in data pipeline implementation in a cloud environment.

Requirements

3+ years of work experience in data pipeline implementation role
Post-secondary degree in a quantitative discipline.
Solid understanding of data ETL/pipeline architecture and implementation.
Strong understanding of cloud architecture – AWS, Microsoft Azure
In-depth knowledge and experience with the following tools: Data extraction – SQL, Python, API invocation Database system e.g., PostgreSQL, Sybase Data storage repositories – SFTP, AWS S3 Scheduling of data jobs – CRON, AWS Step Functions ETL tools – PySpark, AWS Glue, AWS Lambda CI/CD pipelines – Bitbucket/Git, Jenkins, CloudFormation
A strong analytical mindset and sophisticated written and verbal communication skills.
Ability to work within an organization based upon continuous improvement.

Nice To Haves

Experience in the Financial Services Industry is an asset.

Responsibilities

Work with business teams and Data Analysts to understand requirements.
Translate business needs into technical requirements with the support of SMEs.
Recommend efficient and effective data movement architecture base on business needs.
Design, develop, and help maintain data assets to extract, transform, and load data from various internal and external data files, APIs, and databases, and to make them accessible to various client-facing applications as well as data warehouse and internal tools.
Develop and operate highly scalable data pipelines and infrastructure that enable investment analytics, and advisory and client reporting use cases.
Work with QAs and Support teams to resolve issues with new and existing functionalities in production.
Work with Release Management to coordinate deployment of data pipeline changes while adhering to CI deployment standards.
Continue to educate and establish data engineering best practices.