Senior Data Engineer

Senior Data Engineer

Location:

This posting is for an existing vacancy in Wellington-Altus’ Toronto, Winnipeg, or Calgary office.

Founded in 2017, Wellington-Altus Financial Inc. (Wellington-Altus) is the parent company to Wellington-Altus Private Counsel Inc., Wellington-Altus USA Inc., Wellington-Altus Insurance Inc., Wellington-Altus Group Solutions Inc., and Wellington-Altus Private Wealth Inc.

-the top‑rated investment dealer in Canada and one of Canada’s Best Managed Companies. With over $45 billion in assets under administration and offices across the country, Wellington-Altus identifies with successful, entrepreneurial advisors and portfolio managers and their high‑net‑worth clients.

Reporting to the Senior Manager, Data Engineering, the Senior Data Engineer will be responsible for designing, building, and deploying scalable data processing pipelines, and data platform capabilities using the company’s core data technologies, including AWS Glue, Lambda, Athena, Redshift and selected open‑source tools. This role ensures that the data solutions are reliable, efficient, and aligned with established engineering standards and best practices.

The role will collaborate closely with Data Analysts, Quality Assurance, and cross‑functional teams to deliver high‑quality data products, enable new business capabilities, and support data‑driven decision‑making. Additionally, this role will contribute to the evolution of the organization’s data architecture, promote data quality standards, and help build robust data capabilities that support and accelerate the company’s strategic objectives.

• Designing, building and maintaining data pipelines.
• Designing and maintaining data infrastructure and ETL processes based on industry standards and best practices.
• Recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
• Fostering an environment that emphasizes trust, open communication, creative thinking, and cohesive team effort.
• Designing architecture and migrating Microsoft/SQL data systems to AWS cloud.
• Designing data models and automating manual processes.
• Maintaining AWS data infrastructure.
• Maintaining and enforcing quality and service standards, analyzing and resolving issues, identifying trends, and recommending improvements.
• Collaborating with the design team.
• Combining technical expertise and problem‑solving passion to work closely with project teams, turning complex ideas into end‑to‑end solutions that transform our clients’ business.
• Contributing to the design, development and delivery of large‑scale data for mobile adoption and transformation projects that deliver business value for clients.
• Conducting technical feasibility assessments and providing project estimates for the design and development of the solution.
• Providing technical inputs to agile processes, such as epic, story and task definition to resolve issues and remove barriers throughout the lifecycle of client engagements.
• Creation and maintenance of multi‑platform solutions including hybrid environments using tools such as AWS, Dev Ops, Visual Studio and Cloud services.
• Supporting team members in challenging situations (resource / release challenges, cross‑team communication).
• Scheduling ad‑hoc meetings to solve for disagreements or ambiguities to reduce risk of jeopardizing milestones and or artifacts.
• Scheduling and chairing scrum ceremonies.
• Performing other duties as assigned.

• A bachelor's degree in computer science, information management or equivalent experience in a related field(s).
• Minimum of 5 to 7 years of experience with data infrastructure in AWS cloud.
• 4+ years hands‑on experience with AWS stack such as S3, DMS, Glue, EC2, Lambda, Airflow.
• 3+ years of data engineering, including Dev Ops, Data Ops, and MLOps.
• Proficiency with the MSOffice suite, including Word, Excel, PowerPoint, Teams, and Outlook.
• Demonstrable experience with one or more of SQL, R, Python, Spark.
• Experience in building logical and physical design of data, relational/non‑relational databases such as Snowflake/Redshift.
• Experienc…