Business Intelligence Engineer

BFL CANADA•Montreal, QC

2h•Hybrid

About The Position

We are looking for a Business Intelligence Engineer to join our Business Intelligence team in our Montreal, Vancouver or Toronto office! As a Business Intelligence Engineer, you will work with a dedicated team whose goal is to leverage data and provide autonomy, enabling them to make sound data-driven decisions. If you are career-minded and looking for a dynamic work environment with a growth mindset, you will love working among our team!

Requirements

Bachelor’s degree in Computer Science, Statistics, Mathematics, Information Systems, or a related quantitative field
1–2 years of hands-on BI or data experience (internships and university projects with real datasets count)
Strong SQL is non-negotiable — window functions, CTEs, query optimization, and the ability to independently investigate a dataset you've never seen before
Python or R proficiency is required — you should be comfortable using pandas/dplyr, writing reusable scripts, and applying basic statistical reasoning to data problems
Demonstrated ability to break down ambiguous business problems into structured analytical questions — you know what to ask before you start building
Proven attention to data quality — you cross-validate outputs, question unexpected results, and don't ship a number you can't explain
Working knowledge of Power BI including DAX, data modelling, and the Power BI service (RLS, workspaces, deployment pipelines)
Familiarity with dimensional data modelling, data warehouse concepts, and layered/medallion architecture patterns
Able to communicate data findings clearly and concisely to non-technical stakeholders — in both French and English
Intellectually curious, self-directed, and genuinely motivated by turning messy data into clear answers

Nice To Haves

Exposure to Azure data services (Synapse Analytics, Data Factory, Data Lake Storage) is an asset

Responsibilities

Design, build, and maintain Power BI reports, dashboards, and semantic models following enterprise-grade best practices.
Develop and manage Row-Level Security (RLS) implementations across the Power BI environment.
Build and maintain data models, including dimensional and star-schema structures in SQL Server and Azure Synapse.
Write clean, optimized SQL to support reporting pipelines, data transformation, and ad hoc analysis.
Use Python or R to automate data workflows, perform exploratory data analysis, and support ad hoc analytical requests.
Participate in delta/incremental data pipeline development and maintenance alongside Data Engineering.
Translate complex business requirements into scalable reporting solutions across multiple business domains.
Proactively identify gaps in reporting coverage and surface data quality or structural issues upstream.
Contribute to exploratory analytics and data science initiatives within the existing data infrastructure.
Operate within an Agile delivery framework, managing backlog items and sprint deliverables.