Data Engineer

We’re looking for a modern Data Engineer who thrives at the intersection of data, cloud, and AI. You build the systems that power insight - scalable pipelines, cloud-native data platforms, and intelligent workflows that turn raw data into business value at speed. In this role, you’ll architect and own our data infrastructure end-to-end: designing pipelines, optimizing data warehouses on platforms like Snowflake and Redshift, and leveraging AI-assisted tooling and agentic development practices to move faster and smarter. You bring a builder’s mindset, are fluent in modern data stacks, and are energized by a rapidly evolving technology landscape.

This is a full-time, in-person role at our Victoria office.  

What you’ll do:

• Support the building of data acquisition and preparation processes 
• Creating data integration scripts and executing analytical queries that transform and utilize data for business insights 
• Data pipeline maintenance/testing 
• Facilitate data cleansing and data enrichment 
• Identify ways to improve data reliability, efficiency, and quality 
• Prepare data for predictive and prescriptive modeling 
• Support machine learning operations (MLOps) 
• Enable searching, data visualization, and advanced analytics - including building and maintaining dashboards and reports in Tableau and Power BI to drive self-serve analytics across the business 
• Design, build, and maintain a semantic layer of data - a governed, business-ready data foundation that serves as the trusted source for BI, reporting, and AI data agents 
• Work with stakeholders to understand needs for data structure, availability, and accessibility 
• Selecting and integrating any data tools and frameworks required to provide requested capabilities 
• Implement data security and protection practices 
• Designing and developing databases 
• Create technical documentation, such as user manuals, process flow diagrams, system architecture diagrams, etc. 
• Responsible for ensuring the accuracy and quality of data 

What you bring:

EXPERIENCE/TRAINING/EDUCATION:

• At least four years’ experience is preferred.  

COMMUNICATION SKILLS:

• Ability to read, analyze, and interpret general business periodicals, professional journals, technical procedures, or governmental regulations.   
• Ability to write reports, business correspondence, and procedure manuals.   
• Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public.  
• Problem-solving, teamwork, and effective communication with both technical and non-technical audiences are crucial. 

REASONING ABILITY:

High Skills:

• Ability to solve practical problems and deal with a variety of concrete variables in situations where only limited standardization exists.  
• Ability to interpret a variety of instructions furnished in written, oral, diagram, or schedule form. 

MATHEMATICAL SKILLS:

High Skills:

• Ability to work with mathematical concepts such as probability and statistical inference, and fundamentals of plane and solid geometry and trigonometry.   
• Ability to apply concepts such as fractions, percentages, ratios, and proportions to practical situations. 

SKILLS/ABILITIES:

• Knowledge of various ETL techniques and frameworks 
• Strong background with data modeling, data access, and data storage techniques 
• Proficiency in Application Development code like Python, C#, R or Java 
• Strong background to manage the entire back-end development life cycle of a data warehouse 
• Proficiency understanding of Data Store technologies like Relational Databases and NoSQL but not limited to those 
• Knowledge of cloud infrastructure and services like Azure, AWS, or GCP 
• Experience with integration of data from multiple data sources 
• Being able to set up and manage ETL tools and pipelines that support these projects 
• Proficiency understanding of distributed computing principles 
• Proficiency in BI and data visualization tools including Tableau and Power BI 
• Experience with Amazon Redshift and cloud data warehouse technologies 
• Experience with Snowflake, including Snowflake Cortex for AI-powered analytics and data processing 
• Experience applying AI tools and agentic development practices to data engineering workflows - including LLM-assisted pipeline development, AI-powered code generation, and autonomous agent orchestration 

Compensation: $90,000-$120,000 CAD