Business Intelligence Engineer
Role Overview
The role combines data engineering, analytics, and applied AI to build data infrastructure, intelligent workflows, and automated systems.
Works with strategy, sales, and operations teams to identify operational friction and deliver scalable solutions.
Requires business understanding, technical execution, proactive problem-solving, and communication with non-technical partners.
Key Skills for This Role
Full Job Posting
About the role
The role combines data engineering, analytics, and applied AI to build data infrastructure, intelligent workflows, and automated systems.
Works with strategy, sales, and operations teams to identify operational friction and deliver scalable solutions.
Requires business understanding, technical execution, proactive problem-solving, and communication with non-technical partners.
Workplace
- This is a hybrid role, working from the Toronto office twice a week.
Responsibilities
- Partner with cross-functional stakeholders to analyze workflows, identify manual bottlenecks, and define requirements for data models, pipelines, and AI solutions.
- Build and maintain scalable ETL/ELT pipelines, data models, and Python/SQL automations that load data into Snowflake.
- Integrate LLM APIs, RAG tools, vector databases, and agentic workflows to automate business operations and accelerate decisions.
- Create interactive dashboards and visualizations with automated alert triggers and insights for business metrics.
- Develop validation, evaluation, and monitoring frameworks for data and AI quality, reliability, security, and compliance.
- Evaluate orchestration tools, AI frameworks, and data sources to improve analytics capabilities.
- Communicate technical architecture, pipeline logic, and AI outcomes to business partners and leadership.
Minimum qualifications
- Bachelor's or Master's degree in Computer Science, Statistics, Data Science, Information Systems, Economics, or a related quantitative field.
- At least 2 years of hands-on experience in data engineering, business intelligence, or applied analytics.
- Advanced SQL and Python proficiency for data processing, system integration, API development, and data modeling.
- Hands-on experience with cloud data warehouses such as Snowflake and orchestration frameworks such as Airflow or similar ETL tools.
- Familiarity with AI APIs, vector databases, RAG architectures, and frameworks such as LangChain or LlamaIndex.
- Experience designing enterprise dashboards and reports with Superset, MicroStrategy, Tableau, or similar BI tools.
- Excellent written and verbal communication; proactive, curious, and adaptable, with end-to-end project ownership in ambiguous environments.
Benefits and perks
- Work from almost anywhere for up to 20 days per year.
- Company-paid therapy sessions through SpringHealth and a Headspace subscription.
- An annual company-wide week off and paid parental leave.
- The description also mentions generous paid vacation; the provided text ends before further benefit details.
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