WHAT YOU’LL DO

Join our dynamic team dedicated to revolutionizing data infrastructure and products for impactful decision-making at Braze. We collaboratively shape data engineering strategies, optimizing data pipelines and architecture to drive business growth and enhance customer experiences.

Responsibilities:

• Lead the design, implementation, and monitoring of scalable data pipelines and architectures using tools like Snowflake and dbt
• Develop and maintain robust ETL processes to ensure high-quality data ingestion, transformation, and storage
• Collaborate closely with data scientists, analysts, and other engineers to design and implement data solutions that drive customer engagement and retention
• Optimize and manage data flows and integrations across various platforms and applications
• Ensure data quality, consistency, and governance by implementing best practices and monitoring systems
• Work extensively with large-scale event-level data, aggregating and processing it to support business intelligence and analytics
• Implement and maintain data products using advanced techniques and tools
• Collaborate with cross-functional teams including engineering, product management, sales, marketing, and customer success to deliver valuable data solutions
• Continuously evaluate and integrate new data technologies and tools to enhance our data infrastructure and capabilities

WHO YOU ARE

The ideal candidate for this role possesses:

• 5+ years of hands-on experience in data engineering, cloud data warehouses, and ETL development, preferably in a customer-facing environment
• Proven expertise in designing and optimizing data pipelines and architectures
• Strong proficiency in advanced SQL and data modeling techniques
• A track record of leading impactful data projects from conception to deployment
• Effective collaboration skills with cross-functional teams and stakeholders
• In-depth understanding of technical architecture and data flow in a cloud-based environment
• Ability to mentor and guide junior team members on best practices for data engineering and development
• Passion for building scalable data solutions that enhance customer experiences and drive business growth
• Strong analytical and problem-solving skills, with a keen eye for detail and accuracy
• Extensive experience working with and aggregating large event-level data
• Familiarity with data governance principles and ensuring compliance with industry regulations
• Prefer, but don’t require, experience with Kubernetes for container orchestration and Airflow for workflow management

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