Senior Data Engineer

Job Description: Senior/Staff Data Engineer (Contract full-time)

We are currently hiring for a Senior/Staff Data Engineer (Contract full-time) to join our newly formed Data & Analytics Engineering team. This team is dedicated to establishing a robust data & analytics engineering foundation at scale, empowering fast data-driven decision-making for our business partners.

Role Overview:

As a Data Engineer at the Senior/Staff level, you will be responsible for driving data solution architecture and implementation in an agile environment. You will work closely with our business partners and other key stakeholders to deliver high-quality data solutions.

Qualifications:

Minimum of 8 years of software/data engineering experience, including at least 2 years of technical lead experience.

Strong knowledge of data engineering best practices and data architecture patterns, such as Data Mesh and Lakehouse.

Proven experience in end-to-end data architecture and design, preferably with Azure technologies such as Data Factory, Databricks, Delta Lake, Synapse, Purview, and Azure DevOps.

Solid understanding of data modeling fundamentals and expertise in implementing effective data governance practices, including data quality, lineage, and data discovery.

Experience driving CI/CD and laC adoption to automate change management of data pipelines and infrastructure, utilizing tools like Git/GitHub, Jenkins, Terraform, and Ansible.

Deep proficiency in Python and SQL, with experience using PySpark.

Ability to build data exploratory interfaces using Notebooks (e.g., Databricks) and sandbox environments to enable self-service capabilities.

Passion for taking ownership and applying engineering best practices in day-to-day work.

Self-starter and quick learner, always seeking opportunities to drive engineering excellence and never satisfied with the status quo.

Responsibilities:

In this role, your typical day will involve:

Designing and implementing full-stack data and analytics solutions at scale to enhance analytics capabilities.

Independently shipping large and complex features and foundational improvements from start to completion, including requirements/data analysis, development, testing, and deployment.

Building and maintaining data pipelines that ingest, clean, transform, aggregate, and serve structured and unstructured data to meet operational and analytical needs.

Driving data modeling and ensuring proper data quality and integrity checks as part of data pipelines.

Establishing robust infrastructure on Azure to enable self-service data and analytics, advanced data science, and machine learning capabilities for our business users.

Managing complex requirements and technical discussions with minimal oversight, providing architecture recommendations aligned with the technology roadmap and enterprise data strategy.

Continuously seeking opportunities to improve data and code quality, platform performance, and scalability by introducing and implementing engineering best practices and standards.

Location: Toronto/Hybrid (2 days in office + remote)

Contract Duration: 12 months