The Staff Business Intelligence Engineer will collaborate across teams to drive business growth through data analysis and strategic insights, focusing on building data solutions and communicating findings effectively.
Role Description
We're looking for a Staff Business Intelligence Engineer to partner with engineering and product teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.
Responsibilities- Partner Strategically: Collaborate with Data Science, Product, Marketing, Sales, and Engineering teams to understand their goals and challenges. Your work will directly influence decision-making across the organization.
- Build Solutions: Design, develop, and maintain reliable data pipelines and models that turn raw data into meaningful insights. Your work will simplify complex concepts into user-friendly dashboards and visualizations.
- Drive Impact: Identify trends, diagnose problems, and craft solutions using metrics, reporting tools, and predictive models.
- Ensure Quality: Maintain high standards for data governance, privacy, and security while ensuring data quality and reliability.
- Communicate Insights: Translate data into compelling stories, empowering stakeholders at all levels to take action.
- Prioritization: Understand what matters most and prioritize ruthlessly
- Technical Expertise:
- Advanced SQL with hands-on experience building and optimizing data pipelines.
- Knowledge of data modeling best practices (e.g., dimensional modeling).
- Experience with BI tools such as Tableau, Looker, or PowerBI.
- Analytical Mindset: Strong problem-solving skills and the ability to identify key trends in complex datasets.
- Collaboration Skills: A natural communicator who can translate business needs into technical requirements and technical results into actionable business insights.
- Experience:
- 8-10+ years of experience in data science, data engineering, or a similar field.
- Proven track record of delivering data-driven projects that drive meaningful results.
- Familiarity with cloud environments like Snowflake or Databricks is a plus.
- Education: Bachelor’s degree in a quantitative field like Computer Science, Engineering, Math, Statistics, or Economics. Master’s degree is a plus.
Preferred Qualifications
- Master’s or Ph.D. Degree in a quantitative field
- Experience with predictive modeling, Machine Learning, and A/B Testing methods
Canada Pay Range
$181,900—$246,100 CAD
Top Skills
Databricks
Looker
Power BI
Snowflake
SQL
Tableau
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
