Lead Business Analyst I

Responsibilities

• 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.
• 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.

Requirements

• Experie

Additional Information

At Braze, we have found our people. We're a genuinely approachable, exceptionally kind, and intensely passionate crew. We seek to ignite that passion by setting high standards, championing teamwork, and creating work-life harmony as we collectively navigate rapid growth on a global scale while striving for greater equity and opportunity - inside and outside our organization. To flourish here, you must be prepared to set a high bar for yourself and those around you. There is always a way to contribute: Acting with autonomy, having accountability and being open to new perspectives are essential to our continued success. Our deep curiosity to learn and our eagerness to share diverse passions with others gives us balance and injects a one-of-a-kind vibrancy into our culture. If you are driven to solve exhilarating challenges and have a bias toward action in the face of change, you will be empowered to make a real impact here, with a sharp and passionate team at your back. If Braze sounds like a place where you can thrive, we can't wait to meet you. Braze is seeking a Lead Analyst I 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.

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