Lead Data Engineer

Perform•Toronto, ON

72d

About The Position

We are seeking an experienced Data Engineer Lead to support complex application and product development initiatives. This role focuses on designing, building, and leading data migrations, pipelines, and models that power web and mobile software experiences. You will work closely with product and engineering teams in a fast-paced, collaborative environment. This is a hands-on technical leadership role with responsibility across the full data lifecycle — from design through deployment and ongoing support.

Requirements

7+ years of experience in a data-focused engineering role
Strong experience leading data migration initiatives
Proficient in Python with a track record of shipping production pipelines
Strong experience with SQL and NoSQL databases (SQL Server and MongoDB preferred)
Comfortable building scripts or services for data movement and validation
Experience with Azure data tools (such as Azure Data Factory, Azure Data Lake, Microsoft Fabric) or comparable technologies
Experience with Git and distributed version control
Familiar with automated deployments and continuous delivery practices
Strong understanding of REST APIs, JSON, testing, security, and performance best practices
Bachelor’s degree in Computer Science or related field, or equivalent experience
Strong verbal and written communication skills
Thrive in collaborative, service-oriented environments
The successful candidate will be required to work PST hours.

Responsibilities

Lead data engineering execution for complex application initiatives
Design and deliver data migrations between systems, including:
Data mapping and transformation
Validation and reconciliation
Ensuring accuracy and completeness across environments
Build and maintain production-grade data pipelines, APIs, and data management tools
Model data and analyze source and target schemas
Write complex SQL and work with both relational and NoSQL databases
Resolve data quality issues during migrations
Support continuous delivery across the lifecycle: design, build, deploy, test, monitor, and support
Contribute to discussions around data quality, testing strategy, and automation
Collaborate closely with engineers and stakeholders in an agile environment