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Job Description & How to Apply Below
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 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
EXPERIENCE/TRAINING/
EDUCATION:
- At least four years' experience is preferred.
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.
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.
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.
- 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 No
SQL 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 bedeterminedby factors including knowledge and skills, role-specific qualifications, market location, and experience.
Life at Buyerlink:- Take part in our Service Days program - where you'll be rewarded with paid time off for…
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