Braze is seeking a Lead Analyst with a deep background in DBT development and Go-To-Market Analytics to join our Business Analytics team within the broader Growth Data organization.

As Braze scales, we are aggressively modernizing our data infrastructure to serve our Go-To-Market (GTM) teams. We need an experienced practitioner with a proven track record of developing scalable data models who holds themselves to the highest standards of the Modern Data Stack. Sitting within our Business Analytics function, you will work in a tight feedback loop with GTM operators and revenue leaders, operating with significantly more business context than a traditional, siloed data role.

You will serve as a foundational architect for many of our revamped GTM data models—bridging the gap between raw operational data and strategic execution while refactoring legacy models that no longer meet the needs of a scaling business. Though you will spend the vast majority of your time developing models in dbt, you are expected to be a full-cycle practitioner. This means occasionally stepping out of the DAG to perform deep-dive analysis in Python or curate the final Looker experience to ensure your architecture translates into executive action.

Location & Eligibility: You must currently reside in Canada and possess independent work authorization. We cannot provide visa sponsorship or relocation assistance for this role.

Who This Role is NOT For:

• Dashboard Builders: If your primary comfort zone is dragging and dropping in Tableau or PowerBI, and you do not actively write DRY, modular dbt code, this role is not a fit. We are hiring a code-first data architect, not a report builder.
• ML Deployers or Data Scientists: While you will use Python for complex ad-hoc analysis, we are not deploying predictive Machine Learning models into production. If you want to be an ML Engineer, you will be bored here.

WHAT YOU'LL DO

• Data Architecture & Refactoring: 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).
• Strategic GTM Modeling: 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.
• Technical Standards Leadership: 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.
• High-Agency Project Ownership: 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.
• Advanced Analysis: 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.
• BI Layer Execution: Develop LookML models and dashboards as needed to finalize the delivery of your data products. You ensure the visualization layer remains an accurate and performant reflection of the underlying dbt architecture.
• Semantic Governance: Build and maintain a robust semantic layer in dbt to provide strict guardrails for business users, enabling safe, reliable self-service analytics free from metric divergence.

WHO YOU ARE

• Experience: 4–5+ years of dedicated individual contributor experience in data architecture, dbt development, or advanced data modeling.
• Core Technical Proficiency: Expert-level SQL and advanced dbt capabilities are strictly required. You must be heavily experienced in dimensional modeling, utilizing modern cloud data warehouses. Experience with dbt semantic layers is a major plus.
• Strong Data Model and Product Design Acumen: You go beyond delivering the requested specifications given by stakeholders to deliver data products that actually address the underlying business problem. You are capable of translating vaguely defined business problems or processes with little documentation into clearly articulated requirements. When designing models, you account for organizational ambiguity and think several moves ahead to ensure that future projects do not require a full pipeline refactor.
• Analytical Agility: Proficiency in Python (pandas, scikit-learn) to handle ad-hoc analysis, statistical modeling, outlier identification, diagnosing data quality issues, and analytical edge cases.
• Domain Expertise: Deep understanding of B2B SaaS Go-To-Market operations, GTM funnels, and Revenue Operations data modeling. You understand the commercial implications of business data just as deeply as the computational implications of a complex table join.

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between CA$121,700-CA$143,200/year, with an expected On Target Earnings (OTE) between CA$135,200-CA$159,100/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid