Senior Data Engineer
Summary
Senior/Staff Data Engineer (contract, full-time) in Toronto building a new Data & Analytics Engineering team's foundation: designing Azure data architecture, pipelines, modeling, governance, and CI/CD/IaC with tools like Databricks, Data Factory, Python/SQL/PySpark, and Terraform. Hybrid role, 2 days per week in office.
We are currently hiring for a Senior/Staff Data Engineer(Contract full-time) to join our newly formed Data & Analytics Engineeringteam. This team is dedicated toestablishing 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 anagile environment. You will work closely with our business partners and other keystakeholders 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 dataquality, lineage, and data discovery.
Experience driving CI/CD and laC adoption to automate change management of data pipelines and infrastructure, utilizing tools likeGit/GitHub, Jenkins, Terraform, and Ansible.
Deep proficiency in Python and SQL, with experience usingPySpark.
Ability to build data exploratory interfaces using Notebooks(e.g., Databricks) and sandbox environments to enable self-servicecapabilities.
Passion for taking ownership and applying engineering bestpractices in day-to-day work.
Self-starter and quick learner, always seekingopportunities to drive engineering excellence and never satisfied with thestatus quo.
Responsibilities
In this role, your typical day will involve:
Designing and implementing full-stack data and analyticssolutions at scale to enhance analytics capabilities.
Independently shipping large and complex features andfoundational improvements from start to completion, including requirements/dataanalysis, development, testing, and deployment.
Building and maintaining data pipelines that ingest, clean,transform, aggregate, and serve structured and unstructured data to meetoperational and analytical needs.
Driving data modeling and ensuring proper data quality andintegrity checks as part of data pipelines.
Establishing robust infrastructure on Azure to enableself-service data and analytics, advanced data science, and machine learningcapabilities for our business users.
Managing complex requirements and technical discussionswith minimal oversight, providing architecture recommendations aligned with thetechnology roadmap and enterprise data strategy.
Continuously seeking opportunities to improve data and codequality, platform performance, and scalability by introducing and implementingengineering best practices and standards.
Location
Toronto/Hybrid (2 days in office + remote)