Data Engineer

OCS Ontario Cannabis Store•Toronto, ON

37d•CA$82,624 - CA$123,508•Onsite

About The Position

The Ontario Cannabis Store (OCS) is seeking a Data Engineer to join their team. This role involves designing, building, and maintaining scalable data pipelines and architectures to support advanced analytics, reporting, and dashboards. The Data Engineer will transform complex data into reliable, high-quality datasets, enabling informed decision-making by business and analytics teams. The position requires collaboration across the organization to translate business requirements into technical solutions, contributing to the development of modern data platforms and data governance practices.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field, or an equivalent combination of education and experience.
3+ years of experience in data engineering, data warehousing, analytics engineering, or a related field.
Experience designing, building, and maintaining data pipelines and analytics solutions.
Strong experience with Azure data services, including Azure Data Factory, Synapse, Data Lake, and Functions.
Experience with data modeling, schema design, and data warehousing concepts.
Proficiency in SQL and at least one programming language, such as Python.
Working knowledge of BI tools, including Power BI.
Advanced proficiency in Microsoft Excel.
Strong analytical, problem-solving, and critical-thinking skills.
Ability to work independently in a fast-paced, agile environment.
Strong communication and stakeholder management skills.
Ability to translate business requirements into effective technical solutions.

Nice To Haves

Microsoft Azure Data Engineer certification is preferred.
AWS Certified Data Analytics or Data Engineer certification is preferred.
3+ years of experience working with large-scale SQL and NoSQL databases preferred.
1+ year of experience working with distributed systems such as Spark or Hadoop preferred.
3+ years of experience working with cloud platforms such as Azure, AWS, or GCP is an asset.

Responsibilities

Design, build, and maintain batch and real-time data pipelines.
Develop scalable data integration solutions across multiple data sources to support business intelligence and analytics.
Build and optimize ETL/ELT processes using Azure technologies, including Data Factory, Synapse, Functions, and Logic Apps.
Automate data workflows, monitor pipeline performance, and resolve issues as needed.
Implement best practices for data storage, processing, and consumption while adhering to architectural standards.
Translate business requirements into technical designs and data models.
Create and maintain technical and functional documentation.
Communicate complex technical concepts in a clear, actionable manner to support data-driven decision-making.
Collaborate with business, analytics, vendors, and partners to ensure data assets are accessible, well-documented, and aligned with business objectives.
Manage stakeholder priorities and deliver data solutions within agreed timelines.
Enable secure, reliable, and governed data sharing to support integrations and partnerships.
Maintain and enhance the Azure-based data platform and ecosystem.
Manage data ingestion, transformation, and delivery across systems.
Ensure data quality, integrity, and consistency across all data pipelines.
Design and evolve datasets and data structures to meet changing business needs.
Contribute to the continuous improvement of data architecture, platform performance, and scalability.