Senior Data Engineer

Zohorecruit; Toronto; Hybrid; CAD 120,000 - 160,000; Full time

Job summary

Zohorecruit is seeking a Senior/Staff Data Engineer to join our Toronto-based Data & Analytics Engineering team. You will drive data solution architecture, lead initiatives, and deliver scalable data pipelines to empower data-driven decisions.

You will work with Azure technologies (Data Factory, Databricks, Delta Lake, Synapse, Purview) and implement governance, CI/CD, and IaC to standardize data platforms for business partners. This is a hybrid Toronto-based role.

Qualifications

• 8+ years in software/data engineering.
• 2+ years in technical lead roles.
• Experience with Azure data stack and governance.

Responsibilities

• Design full-stack data and analytic solutions at scale.
• Ship large, complex features from start to finish including requirements, development, testing and deployment.
• Build and maintain data pipelines for structured and unstructured data.
• Drive data modeling and ensure data quality and lineage checks.
• Establish Azure-based infrastructure for self-service analytics and ML capabilities.
• Collaborate with stakeholders to align with data strategy and architecture roadmaps.
• Improve data quality and platform performance through engineering best practices.

Skills

Data engineering

Technical leadership

Azure Data Factory

Databricks

Delta Lake

Azure Synapse

Purview

Git/GitHub

Jenkins

Terraform

Ansible

Python

SQL

PySpark

Notebooks

Data governance

Data modeling

CI/CD

IaC

Tools

Azure DevOps

Job description

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)