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
• Robust 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 Compensation will be determined by factors including knowledge and skills, role-specific qualifications, market location, and experience.

📌 Data Engineer (Victoria)
🏢 Buyerlink
📍 Victoria