Lead Business Analyst I

Braze Braze · Enterprise · Toronto, ON · Growth

Lead Business Analyst with deep background in DBT development and Go-To-Market Analytics. The role involves modernizing data infrastructure, developing scalable data models using dbt, and bridging the gap between raw operational data and strategic execution. Responsibilities include data architecture, refactoring legacy models, leading GTM data models, setting technical standards, project ownership, advanced analysis in Python, and BI layer execution. The role explicitly states it is NOT for dashboard builders or ML deployers/data scientists.

What you'd actually do

  1. Lead the deprecation of legacy, undocumented reporting layers. Design, deploy, and govern highly modular, scalable data pipelines using advanced dbt methodologies (Jinja, custom macros, incremental materializations, and robust testing).
  2. Act as a key architect for our GTM data models. Untangle underserved operational processes and translate them into scalable, reliable data products that expand beyond basic Salesforce objects.
  3. Serve as a senior DBT practitioner by reviewing PRs, providing technical mentorship, and elevating the team's development baseline through rigorous code standards. Thoughtfully leverage AI to automate rote tasks (style compliance, docs) to free up time for higher-leverage work.
  4. Drive the end-to-end execution of strategic analytics initiatives by interfacing directly with a complex matrix of stakeholders—including Data Engineering, Business Systems, GTM Operations, and Salesforce Administrators. You are expected to proactively capture the technical reality of their workflows, scope solutions from first principles, and design the models that constrain and optimize organizational decision-making with minimal supervision.
  5. Utilize Python (pandas, scikit-learn) for complex analytical needs—such as evaluating lead scoring or the impact of GTM touchpoints on pipeline conversion—that exceed the limits of SQL. You surface signals from operational processes to drive GTM efficiency.

Skills

Required

  • DBT development
  • Go-To-Market Analytics
  • data architecture
  • advanced data modeling
  • SQL
  • dbt
  • dimensional modeling
  • cloud data warehouses
  • Python
  • pandas
  • scikit-learn

Nice to have

  • dbt semantic layers

What the JD emphasized

  • code-first data architect
  • not deploying predictive Machine Learning models into production
  • strictly required
  • Expert-level SQL and advanced dbt capabilities are strictly required