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.

WHAT YOU’LL DO

Join our passionate Data Engineering team focused on building and maintaining robust data pipelines and products that enable better decision-making across Braze. You’ll work alongside talented engineers and stakeholders across the business to support data infrastructure, develop reliable workflows, and implement data processes that scale with our growth.

Responsibilities:

• Own and maintain complex multi-step data pipelines using tools like DBT, Snowflake, and Python
• Design and document data process flows and SLAs within your department
• Build scalable ETL processes that ensure reliable ingestion, transformation, and delivery of key datasets
• Support data integrations and workflows between internal systems and external tools
• Work with stakeholders to understand requirements and translate them into data models and pipelines
• Develop data tests and monitoring processes to ensure data quality and consistency
• Improve performance and reliability of existing workflows using CI/CD, orchestration tools, and optimization techniques
• Proactively identify and implement improvements to departmental data structures and infrastructure
• Support junior team members through mentoring and code reviews

The ideal candidate for this role possesses:

• 2–4 years of experience in data engineering, preferably with cloud-based data platforms
• Proficiency in SQL and one or more programming languages such as Python or Java
• Hands-on experience with modern data tools like dbt, Snowflake, Airflow, or similar technologies
• Familiarity with building and maintaining scalable ETL pipelines
• Understanding of data modeling concepts and principles of data governance
• Ability to communicate clearly with technical and non-technical stakeholders
• A collaborative mindset and the ability to anticipate data needs across departments
• Willingness to mentor junior engineers and contribute to engineering standards
• Preferred but not required: Experience with Kubernetes or other orchestration framework